Tackling Climate Change with Machine Learning

Costs of mitigating CO2 emissions from passenger aircraft

Andreas W. Schäfer, Antony D. Evans, Tom G. Reynolds, and Lynnette Dray · 2015

Cited alongside, same era.

Managing electric vehicles in the smart grid using artificial intelligence: A survey

E. S. Rigas, S. D. Ramchurn, and N. Bassiliades · 2015

Cited alongside, same era.

Is there a near-term market for vehicle-to-grid electric vehicles?

Michael K. Hidrue and George R. Parsons · 2015

Cited alongside, same era.

Comparison of life cycle greenhouse gases from natural gas pathways for medium and heavy-duty vehicles

Fan Tong, Paulina Jaramillo, and Inês M. L. Azevedo · 2015

Cited alongside, same era.

Predicting travel mode of individuals by machine learning

Hichem Omrani · 2015

Cited alongside, same era.

Incentivizing users for balancing bike sharing systems

Adish Singla, Marco Santoni, Gÿbor Bartók, Pratik Mukerji, Moritz Meenen, and Andreas Krause · 2015

Cited alongside, same era.

How machine learning contributes to smarter pipeline maintenance

Tim Edward and Rob Salkowitz · 2018

Later among the works it cites.

Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning

Van Nhan Nguyen, Robert Jenssen, and Davide Roverso · 2018

Later among the works it cites.

Climate change and power security: Power load prediction for rural electrical microgrids using long short term memory and artificial neural networks

Martin Cenek, Rocco Haro, Brandon Sayers, and Jifeng Peng · 2018

Later among the works it cites.

Forecasting energy demand for microgrids over multiple horizons

Fred Otieno, Nathan Williams, and Patrick McSharry · 2018

Later among the works it cites.

Learning with weak supervision from physics and data-driven constraints

Hongyu Ren, Russell Stewart, Jiaming Song, Volodymyr Kuleshov, and Stefano Ermon · 2018

Later among the works it cites.

Neural ordinary differential equations

Tian Qi Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 2018

Later among the works it cites.

Spnets: Differentiable fluid dynamics for deep neural networks

Original

Connor Schenck and Dieter Fox · 2018

Later among the works it cites.

End-to-end differentiable physics for learning and control

Filipe de Avila Belbute-Peres, Kevin Smith, Kelsey Allen, Josh Tenenbaum, and J Zico Kolter · 2018

Later among the works it cites.

Net-zero emissions energy systems

Steven J. Davis, Nathan S. Lewis, Matthew Shaner, Sonia Aggarwal, Doug Arent, Inês L. Azevedo, Sally M. Benson, Thomas Bradley, Jack Brouwer, Yet-Ming Chiang, Christopher T. M. Clack, Armond Cohen, Stephen Doig, Jae Edmonds, Paul Fennell, Christopher B. Field, Bryan Hannegan, Bri-Mathias Hodge, Martin I. Hoffert, Eric Ingersoll, Paulina Jaramillo, Klaus S. Lackner, Katharine J. Mach, Michael Mastrandrea, Joan Ogden, Per F. Peterson, Daniel L. Sanchez, Daniel Sperling, Joseph Stagner, Jessika E. Trancik, Chi-Jen Yang, and Ken Caldeira · 2018

Later among the works it cites.

Decarbonizing intraregional freight systems with a focus on modal shift

Lynn H Kaack, Parth Vaishnav, M Granger Morgan, Inês L Azevedo, and Srijana Rai · 2018

Later among the works it cites.

Assessing carbon emissions from road transport through traffic flow estimators

Silvio Nocera, Cayetano Ruiz-Alarcón-Quintero, and Federico Cavallaro · 2018

Later among the works it cites.

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

H. M. Abdul Aziz and Satish V. Ukkusuri · 2018

Later among the works it cites.

A generative model of urban activities from cellular data

M. Yin, M. Sheehan, S. Feygin, J. Paiement, and A. Pozdnoukhov · 2018

Later among the works it cites.

Estimating multi-year 24/7 origin-destination demand using high-granular multi-source traffic data

Wei Ma and Zhen (Sean) Qian · 2018

Later among the works it cites.

Spatiotemporal traffic forecasting: review and proposed directions

Alireza Ermagun and David Levinson · 2018

Later among the works it cites.

Spatial transferability of neural network models in travel demand modeling

Liang Tang, Chenfeng Xiong, and Lei Zhang · 2018

Later among the works it cites.

Short-term origin-destination based metro flow prediction with probabilistic model selection approach

Xiaoqing Dai, Lijun Sun, and Yanyan Xu · 2018

Later among the works it cites.

Real time transit demand prediction capturing station interactions and impact of special events

Peyman Noursalehi, Haris N. Koutsopoulos, and Jinhua Zhao · 2018

Later among the works it cites.

Spatiotemporal variation in travel regularity through transit user profiling

Ed Manley, Chen Zhong, and Michael Batty · 2018

Later among the works it cites.

A roadmap toward airport demand and capacity management

Alexandre Jacquillat and Amedeo R. Odoni · 2018

Later among the works it cites.

Multiagent spatial simulation of autonomous taxis for urban commute: Travel economics and environmental impacts

Miaojia Lu, Morteza Taiebat, Ming Xu, and Shu-Chien Hsu · 2018

Later among the works it cites.

Machine Learning for Combinatorial Optimization: a Methodological Tour d’Horizon

Original

Yoshua Bengio, Andrea Lodi, and Antoine Prouvost · 2018

Later among the works it cites.

Artificial intelligence in logistics: a collaborative report by DHL and IBM on implications and use cases for the logistics industry

Ben Gesing and D. Peterson, S. and Michelsen · 2018

Later among the works it cites.

Crystal graph convolutional neural networks for an accurate and interpretable prediction of material properties

Tian Xie and Jeffrey C. Grossman · 2018

Later among the works it cites.

Towards optimal power management of hybrid electric vehicles in real-time: A review on methods, challenges, and state-of-the-art solutions

Ahmed M. Ali and Dirk Söffker · 2018

Later among the works it cites.

A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses

Raul Yondo, Esther Andrés, and Eusebio Valero · 2018

Later among the works it cites.

Anomaly detection and classification in a laser powder bed additive manufacturing process using a trained computer vision algorithm

L. Scime and J. Beuth · 2018

Later among the works it cites.

Acoustic emission for in situ quality monitoring in additive manufacturing using spectral convolutional neural networks

S.A. Shevchik, C. Kenel, C. Leinenbach, and K. Wasmer · 2018

Later among the works it cites.

Bioinspired hierarchical composite design using machine learning: Simulation, additive manufacturing, and experiment

G.X. Gu, C.-T. Chen, D.J. Richmond, and M.J. Buehler · 2018

Later among the works it cites.

Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery

Joshuah K. Stolaroff, Constantine Samaras, Emma R. O’Neill, Alia Lubers, Alexandra S. Mitchell, and Daniel Ceperley · 2018

Later among the works it cites.

Modelling the effect of driving events on electrical vehicle energy consumption using inertial sensors in smartphones

David Jiménez, Sara Hernández, Jesús Fraile-Ardanuy, Javier Serrano, Rubén Fernández, and Federico Álvarez · 2018

Later among the works it cites.

Data-driven optimized layout of battery electric vehicle charging infrastructure

Ye Tao, Miaohua Huang, and Lan Yang · 2018

Later among the works it cites.

A new method for determining the concentration of electrolyte components in lithium-ion cells, using fourier transform infrared spectroscopy and machine learning

LD Ellis, S Buteau, Samuel G Hames, LM Thompson, DS Hall, and JR Dahn · 2018

Later among the works it cites.

Electrofuels for the transport sector: A review of production costs

Selma Brynolf, Maria Taljegard, Maria Grahn, and Julia Hansson · 2018

Later among the works it cites.

Batteries and fuel cells for emerging electric vehicle markets

Zachary P. Cano, Dustin Banham, Siyu Ye, Andreas Hintennach, Jun Lu, Michael Fowler, and Zhongwei Chen · 2018

Later among the works it cites.

Analyzing high speed rail passengers’ train choices based on new online booking data in china

Yanshuo Sun, Zhibin Jiang, Jinjing Gu, Min Zhou, Yeming Li, and Lei Zhang · 2018

Later among the works it cites.

Inferring transportation modes from gps trajectories using a convolutional neural network

Sina Dabiri and Kevin Heaslip · 2018

Later among the works it cites.

A decision support approach for condition-based maintenance of rails based on big data analysis

Ali Jamshidi, Siamak Hajizadeh, Zhou Su, Meysam Naeimi, Alfredo Núñez, Rolf Dollevoet, Bart De Schutter, and Zili Li · 2018

Later among the works it cites.

Track geometry degradation and maintenance modelling: A review

Iman Soleimanmeigouni, Alireza Ahmadi, and Uday Kumar · 2018

Later among the works it cites.

Hybrid cluster-regression approach to model bikeshare station usage

Michael Hyland, Zihan Hong, Helen Karla Ramalho de Farias Pinto, and Ying Chen · 2018

Later among the works it cites.

Prediction of arrival times of freight traffic on US railroads using support vector regression

William Barbour, Juan Carlos Martinez Mori, Shankara Kuppa, and Daniel B. Work · 2018

Later among the works it cites.

An overload behavior detection system for engineering transport vehicles based on deep learning

L. Zhou and G. Wu · 2018

Later among the works it cites.

A review of data-driven building energy consumption prediction studies

Kadir Amasyali and Nora M. El-Gohary · 2018

Later among the works it cites.

Modeling techniques used in building HVAC control systems: A review

Zakia Afroz, GM Shafiullah, Tania Urmee, and Gary Higgins · 2018

Later among the works it cites.

Deep belief network based ensemble approach for cooling load forecasting of air-conditioning system

Guoyin Fu · 2018

Later among the works it cites.

Gigawatt-hour scale savings on a budget of zero: Deep reinforcement learning based optimal control of hot water systems

Hussain Kazmi, Fahad Mehmood, Stefan Lodeweyckx, and Johan Driesen · 2018

Later among the works it cites.

Towards occupant activity driven smart buildings via wifi-enabled iot devices and deep learning

Han Zou, Yuxun Zhou, Jianfei Yang, and Costas J Spanos · 2018

Later among the works it cites.

Time series-based GHG emissions prediction for smart homes

Ana Carolina Riekstin, Antoine Langevin, Thomas Dandres, Ghyslain Gagnon, and Mohamed Cheriet · 2018

Later among the works it cites.

Cross-Cultural Design. Applications in Cultural Heritage, Creativity and Social Development: 10th International Conference, CCD 2018, Held as Part of HCI International 2018, Las Vegas, NV, USA, July 15-20, 2018, Proceedings

Pei-Luen Patrick Rau · 2018

Later among the works it cites.

Controlling district heating and cooling networks to unlock flexibility: A review

Annelies Vandermeulen, Bram van der Heijde, and Lieve Helsen · 2018

Later among the works it cites.

Pattern recognition in building energy performance over time using energy benchmarking data

Sokratis Papadopoulos, Bartosz Bonczak, and Constantine E Kontokosta · 2018

Later among the works it cites.

Estimating residential energy consumption in metropolitan areas: A microsimulation approach

Wenwen Zhang, Caleb Robinson, Subhrajit Guhathakurta, Venu M. Garikapati, Bistra Dilkina, Marilyn A. Brown, and Ram M. Pendyala · 2018

Later among the works it cites.

A geoprocessing framework to compute urban indicators: The MApUCE tools chain

Erwan Bocher, Gwendall Petit, Jérémy Bernard, and Sylvain Palominos · 2018

Later among the works it cites.

Data-driven urban energy simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow

Alex Nutkiewicz, Zheng Yang, and Rishee K Jain · 2018

Later among the works it cites.

Soft sensing in smart cities: Handling 3vs using recommender systems, machine intelligence, and data analytics

H. Habibzadeh, A. Boggio-Dandry, Z. Qin, T. Soyata, B. Kantarci, and H. T. Mouftah · 2018

Later among the works it cites.

Sequences of purchases in credit card data reveal lifestyles in urban populations

Riccardo Di Clemente, Miguel Luengo-Oroz, Matias Travizano, Sharon Xu, Bapu Vaitla, and Marta C González · 2018

Later among the works it cites.

Social-media data for urban sustainability

Rositsa T Ilieva and Timon McPhearson · 2018

Later among the works it cites.

Mobility data specification

City of Los Angeles · 2018

Later among the works it cites.

Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in oslo

Chuan Ding, Xinyu Jason Cao, and Petter Næss · 2018

Later among the works it cites.

A scenario-based approach for assessing the energy performance of urban development pathways

Mafalda Silva, Vítor Leal, Vítor Oliveira, and Isabel M Horta · 2018

Later among the works it cites.

The urban south and the predicament of global sustainability

Harini Nagendra, Xuemei Bai, Eduardo S Brondizio, and Shuaib Lwasa · 2018

Later among the works it cites.

Six research priorities for cities and climate change, 2018

Xuemei Bai, Richard J Dawson, Diana Ürge-Vorsatz, Gian C Delgado, Aliyu Salisu Barau, Shobhakar Dhakal, David Dodman, Lykke Leonardsen, Valérie Masson-Delmotte, Debra C Roberts, et al · 2018

Later among the works it cites.

Making concrete change, innovation in low-carbon cement and concrete

Johanna Lehne and Felix Preston · 2018

Later among the works it cites.

Optimization of process parameters for powder bed fusion additive manufacturing by combination of machine learning and finite element method: A conceptual framework

Ivanna Baturynska, Oleksandr Semeniuta, and Kristian Martinsen · 2018

Later among the works it cites.

The cost of reducing greenhouse gas emissions

Kenneth Gillingham and James H Stock · 2018

Later among the works it cites.

Approximate model predictive building control via machine learning

Ján Drgoňa, Damien Picard, Michal Kvasnica, and Lieve Helsen · 2018

Later among the works it cites.

Digital twin-driven product design, manufacturing and service with big data

Fei Tao, Jiangfeng Cheng, Qinglin Qi, Meng Zhang, He Zhang, and Fangyuan Sui · 2018

Later among the works it cites.

Deep reinforcement learning that matters

Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, and David Meger · 2018

Later among the works it cites.

Detection of methane plumes using airborne midwave infrared (3–5

Rebecca Scafutto and Carlos de Souza Filho · 2018

Later among the works it cites.

Machine learning in agriculture: A review

Konstantinos Liakos, Patrizia Busato, Dimitrios Moshou, Simon Pearson, and Dionysis Bochtis · 2018

Later among the works it cites.

Open digital mapping as a cost-effective method for mapping peat thickness and assessing the carbon stock of tropical peatlands

Budiman Minasny, Budi Indra Setiawan, Satyanto Krido Saptomo, Alex B McBratney, et al · 2018

Later among the works it cites.

A new global peatland map expected for 2020

Claudia Windeck · 2018

Later among the works it cites.

Using spatial reinforcement learning to build forest wildfire dynamics models from satellite images

Sriram Ganapathi Subramanian and Mark Crowley · 2018

Later among the works it cites.

Combining MCTS and A3C for prediction of spatially spreading processes in forest wildfire settings

Sriram Ganapathi Subramanian and Mark Crowley · 2018

Later among the works it cites.

Direct air capture of carbon dioxide: ICEF roadmap 2018

David Sandalow, Julio Friedmann, and Colin McCormick · 2018

Later among the works it cites.

Negative emissions part 1: Research landscape and synthesis

Jan C Minx, William F Lamb, Max W Callaghan, Sabine Fuss, Jerome Hilaire, Felix Creutzig, Thorben Amann, Tim Beringer, Wagner de Oliveira Garcia, Jens Hartmann, et al · 2018

Later among the works it cites.

Negative emissions part 2: Costs, potentials and side effects

Sabine Fuss, William F Lamb, Max W Callaghan, Jérôme Hilaire, Felix Creutzig, Thorben Amann, Tim Beringer, Wagner de Oliveira Garcia, Jens Hartmann, Tarun Khanna, et al · 2018

Later among the works it cites.

Negative emissions part 3: Innovation and upscaling

Gregory F Nemet, Max W Callaghan, Felix Creutzig, Sabine Fuss, Jens Hartmann, Jérôme Hilaire, William F Lamb, Jan C Minx, Sophia Rogers, and Pete Smith · 2018

Later among the works it cites.

Surface functionalization and manipulation of mesoporous silica adsorbents for improved removal of pollutants: a review

Veronica B Cashin, Daniel S Eldridge, Aimin Yu, and Dongyuan Zhao · 2018

Later among the works it cites.

Deep-learning tomography

Mauricio Araya-Polo, Joseph Jennings, Amir Adler, and Taylor Dahlke · 2018

Later among the works it cites.

Geologic co 2 sequestration monitoring design: A machine learning and uncertainty quantification based approach

Bailian Chen, Dylan R Harp, Youzuo Lin, Elizabeth H Keating, and Rajesh J Pawar · 2018

Later among the works it cites.

Could machine learning break the convection parameterization deadlock?

P Gentine, M Pritchard, S Rasp, G Reinaudi, and G Yacalis · 2018

Later among the works it cites.

Deep learning to represent subgrid processes in climate models

Stephan Rasp, Michael S Pritchard, and Pierre Gentine · 2018

Later among the works it cites.

Using machine learning to build temperature-based ozone parameterizations for climate sensitivity simulations

Peer Nowack, Peter Braesicke, Joanna Haigh, Nathan Luke Abraham, and John Pyle · 2018

Later among the works it cites.

Machine learning predictions of a multiresolution climate model ensemble

Gemma Anderson and Donald D Lucas · 2018

Later among the works it cites.

S2S reboot: an argument for greater inclusion of machine learning in subseasonal to seasonal forecasts

Judah Cohen, Dim Coumou, Jessica Hwang, Lester Mackey, Paulo Orenstein, Sonja Totz, and Eli Tziperman · 2018

Later among the works it cites.

Exascale deep learning for climate analytics

Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett Phillips, Ankur Mahesh, Michael Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, and Michael Houston · 2018

Later among the works it cites.

Patterns of geomorphic processes across deltas using image analysis and machine learning

MC Perignon, P Passalacqua, TM Jarriel, JM Adams, and I Overeem · 2018

Later among the works it cites.

Hidden physics models: machine learning of nonlinear partial differential equations

Maziar Raissi and George Em Karniadakis · 2018

Later among the works it cites.

Bootstrapping parameter space exploration for fast tuning

Jayaraman Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Giminez, Rahul Sridhar, Marathe Aniruddha, Tao Wang, Mural Emani, Abhinav Bhatele, and Todd Gamblin · 2018

Later among the works it cites.

Machine learning for applications for Earth observation

D J Lary, G K Zewdie, X Liu, D Wu, E Levetin, Allee R J, Nabin Malakar, A Walker, H Mussa, Mannino A, and Aurin D · 2018

Later among the works it cites.

Label super-resolution networks

Kolya Malkin, Caleb Robinson, Le Hou, Rachel Soobitsky, Jacob Czawlytko, Dimitris Samaras, Joel Saltz, Lucas Joppa, and Nebojsa Jojic · 2018

Later among the works it cites.

Annotation automatique d’images: le cas de la déforestation

Duy Huynh and Nathalie Neptune · 2018

Later among the works it cites.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Xiaohui Feng, María Uriarte, Grizelle González, Sasha Reed, Jill Thompson, Jess K Zimmerman, and Lora Murphy · 2018

Later among the works it cites.

Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning

Mohammad Sadegh Norouzzadeh, Anh Nguyen, Margaret Kosmala, Alexandra Swanson, Meredith S Palmer, Craig Packer, and Jeff Clune · 2018

Later among the works it cites.

Convolutional neural networks predict fish abundance from underlying coral reef texture

Grace Young, Vassileios Balntas, and Victor Prisacariu · 2018

Later among the works it cites.

Systems and methods for electronically identifying plant species, November 8 2018

Eric Ralls · 2018

Later among the works it cites.

Machine learning to analyze the social-ecological impacts of natural resource policy: insights from community forest management in the indian himalaya

Pushpendra Rana and Daniel C Miller · 2018

Later among the works it cites.

The role of restoration and key ecological invasion mechanisms in optimal spatial-dynamic management of invasive species

Heidi J Albers, Kim Meyer Hall, Katherine D Lee, Majid Alkaee Taleghan, and Thomas G Dietterich · 2018

Later among the works it cites.

Infrastructure resilience for climate adaptation

Amrita Gupta, Caleb Robinson, and Bistra Dilkina · 2018

Later among the works it cites.

Ml for flood forecasting at scale

Ami Wiesel, Avinatan Hassidim, Gal Elidan, Guy Shalev, Mor Schlesinger, Oleg Zlydenko, Ran El-Yaniv, Sella Nevo, Yossi Matias, Yotam Gigi, et al · 2018

Later among the works it cites.

Infrastructure quality assessment in africa using satellite imagery and deep learning

Barak Oshri, Annie Hu, Peter Adelson, Xiao Chen, Pascaline Dupas, Jeremy Weinstein, Marshall Burke, David Lobell, and Stefano Ermon · 2018

Later among the works it cites.

Multi-dimensional infrastructure resilience modeling: An application to hurricane-prone electric power distribution systems

Roshanak Nateghi · 2018

Later among the works it cites.

Design and development of reverse osmosis (RO) plant status monitoring system for early fault prediction and predictive maintenance

Satyam Srivastava, Saikrishna Vaddadi, Pankaj Kumar, and Shashikant Sadistap · 2018

Later among the works it cites.

Deep transfer learning for crop yield prediction with remote sensing data

Anna X Wang, Caelin Tran, Nikhil Desai, David Lobell, and Stefano Ermon · 2018

Later among the works it cites.

Accelerating science with generative adversarial networks: an application to 3D particle showers in multilayer calorimeters

Michela Paganini, Luke de Oliveira, and Benjamin Nachman · 2018

Later among the works it cites.

Improving refugee integration through data-driven algorithmic assignment

Kirk Bansak, Jeremy Ferwerda, Jens Hainmueller, Andrea Dillon, Dominik Hangartner, Duncan Lawrence, and Jeremy Weinstein · 2018

Later among the works it cites.

Humanitarian applications of machine learning with remote-sensing data: review and case study in refugee settlement mapping

John A Quinn, Marguerite M Nyhan, Celia Navarro, Davide Coluccia, Lars Bromley, and Miguel Luengo-Oroz · 2018

Later among the works it cites.

Data fusion to describe and quantify search and rescue operations in the Mediterranean sea

Katherine Hoffmann Pham, Jeremy Boy, and Miguel Luengo-Oroz · 2018

Later among the works it cites.

Intelligent drone swarm for search and rescue operations at sea

Original

Vincenzo Lomonaco, Angelo Trotta, Marta Ziosi, Juan De Dios Yáñez Ávila, and Natalia Díaz-Rodríguez · 2018

Later among the works it cites.

Water quality monitoring system using IoT and machine learning

Nikhil Kumar Koditala and Purnendu Shekar Pandey · 2018

Later among the works it cites.

Machine learning approach for spatially and temporally resolved PM2.5 exposures in the continental United States

Qian Di, Petros Koutrakis, Christine Choirat, Francesca Dominici, and Joel D Schwartz · 2018

Later among the works it cites.

OP III–4 exposure assessment models for NO2 and PM2.5 in the elapse study: a comparison of supervised linear regression and machine learning approaches, 2018

Jie Chen, Kees de Hoogh, Maciek Strak, Jules Kerckhoffs, Roel Vermeulen, Bert Brunekreef, and Gerard Hoek · 2018

Later among the works it cites.

From satellite imagery to disaster insights

Original

Jigar Doshi, Saikat Basu, and Guan Pang · 2018

Later among the works it cites.

Machine-assisted map editing

Favyen Bastani, Songtao He, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, and Sam Madden · 2018

Later among the works it cites.

The science and technology of solar geoengineering: A compact summary

David Keith and Peter Irvine · 2018

Later among the works it cites.

The risk of termination shock from solar geoengineering

Andy Parker and Peter J Irvine · 2018

Later among the works it cites.

Production of sulfates onboard an aircraft: implications for the cost and feasibility of stratospheric solar geoengineering

Jordan P Smith, John A Dykema, and David W Keith · 2018

Later among the works it cites.

Quantifying the impact of sulfate geoengineering on mortality from air quality and UV-B exposure

Sebastian D Eastham, Debra K Weisenstein, David W Keith, and Steven RH Barrett · 2018

Later among the works it cites.

Estimating global agricultural effects of geoengineering using volcanic eruptions

Jonathan Proctor, Solomon Hsiang, Jennifer Burney, Marshall Burke, and Wolfram Schlenker · 2018

Later among the works it cites.

Quantifying uncertainty from aerosol and atmospheric parameters and their impact on climate sensitivity

Christopher G Fletcher, Ben Kravitz, and Bakr Badawy · 2018

Later among the works it cites.

The engineering of climate engineering

Douglas G MacMartin and Ben Kravitz · 2018

Later among the works it cites.

Machine learning in control systems: An overview of the state of the art

Signe Moe, Anne Marthine Rustad, and Kristian G Hanssen · 2018

Later among the works it cites.

Finite-data performance guarantees for the output-feedback control of an unknown system

Ross Boczar, Nikolai Matni, and Benjamin Recht · 2018

Later among the works it cites.

Differentiable MPC for end-to-end planning and control

Brandon Amos, Ivan Jimenez, Jacob Sacks, Byron Boots, and J Zico Kolter · 2018

Later among the works it cites.

Using deep learning to model potential impacts of geoengineering via solar radiation management on US agriculture

A Crane-Droesch, B Kravitz, and JT Abatzoglou · 2018

Later among the works it cites.

Climate Change Needs Behavior Change: Making the case for behavioral solutions to reduce global warming

K. Williamson, A. Satre-Meloy, K. Velasco, and K. Green · 2018

Later among the works it cites.

Making carbon pricing work for citizens

David Klenert, Linus Mattauch, Emmanuel Combet, Ottmar Edenhofer, Cameron Hepburn, Ryan Rafaty, and Nicholas Stern · 2018

Later among the works it cites.

Estimating the marginal carbon intensity of electricity with machine learning

Olivier Corradi · 2018

Later among the works it cites.

On-line building energy optimization using deep reinforcement learning

Elena Mocanu, Decebal Constantin Mocanu, Phuong H Nguyen, Antonio Liotta, Michael E Webber, Madeleine Gibescu, and Johannes G Slootweg · 2018

Later among the works it cites.

Residential load scheduling with renewable generation in the smart grid: A reinforcement learning approach

T Remani, EA Jasmin, and TP Imthias Ahamed · 2018

Later among the works it cites.

Assessing the relative importance of psychological and demographic factors for predicting climate and environmental attitudes

Liam F Beiser-McGrath and Robert A Huber · 2018

Later among the works it cites.

A graph-based model to discover preference structure from choice data

Cristóbal De La Maza, Alex Davis, Cleotilde Gonzalez, and Inês Azevedo · 2018

Later among the works it cites.

Renewable energy will be consistently cheaper than fossil fuels by 2020, report claims

Dominic Dudley · 2018

Later among the works it cites.

Supporting energy technology deployment while avoiding unintended technological lock-in: a policy design perspective

Leonore Haelg, Marius Waelchli, and Tobias S Schmidt · 2018

Later among the works it cites.

Evolutionary climate-change modelling: A multi-agent climate-economic model

Sylvie Geisendorf · 2018

Later among the works it cites.

Agent-based modeling of environment-migration linkages: a review

Jule Thober, Nina Schwarz, and Kathleen Hermans · 2018

Later among the works it cites.

Evolutionary model discovery of causal factors behind the socio-agricultural behavior of the ancestral pueblo, 2018

Chathika Gunaratne, Ivan Garibay, and Nguyen Dang · 2018

Later among the works it cites.

Evolution of cooperation in stochastic games

Christian Hilbe, Štěpán Šimsa, Krishnendu Chatterjee, and Martin A. Nowak · 2018

Later among the works it cites.

Intrinsic social motivation via causal influence in multi-agent RL

Original

Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, and Nando de Freitas · 2018

Later among the works it cites.

Tree-based ensemble methods for sensitivity analysis of environmental models: A performance comparison with sobol and morris techniques

Marc Jaxa-Rozen and Jan Kwakkel · 2018

Later among the works it cites.

Machine learning for continuous-time economics

Victor Duarte · 2018

Later among the works it cites.

Assessment of mitigation strategies as tools for risk management under future uncertainties: a multi-model approach

Shunsuke Mori, Toyoaki Washida, Atsushi Kurosawa, and Toshihiko Masui · 2018

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Efficiently optimizing for dendritic connectivity on tree-structured networks in a multi-objective framework

Qinru Shi, Jonathan M. Gomes-Selman, Roosevelt García-Villacorta, Suresh Sethi, Alexander S. Flecker, and Carla P. Gomes · 2018

Later among the works it cites.

Analysis and forecasting of the carbon price using multi—resolution singular value decomposition and extreme learning machine optimized by adaptive whale optimization algorithm

Wei Sun and Chongchong Zhang · 2018

Later among the works it cites.

A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting

Bangzhu Zhu, Shunxin Ye, Ping Wang, Kaijian He, Tao Zhang, and Yi-Ming Wei · 2018

Later among the works it cites.

Carbon pricing prediction based on wavelet transform and K-ELM optimized by bat optimization algorithm in China ETS: the case of Shanghai and Hubei carbon markets

Sun Wei, Zhang Chongchong, and Sun Cuiping · 2018

Later among the works it cites.

How to optimize the development of carbon trading in China – enlightenment from evolution rules of the EU carbon price

Guochang Fang, Lixin Tian, Menghe Liu, Min Fu, and Mei Sun · 2018

Later among the works it cites.

Optimal choice of enterprise’s production strategy under constraints of carbon quota

Xiping Zheng, Qiang Guo, Zenglu Li, and Ting Zhang · 2018

Later among the works it cites.

Learning cognitive models using neural networks

Devendra Singh Chaplot, Christopher MacLellan, Ruslan Salakhutdinov, and Kenneth Koedinger · 2018

Later among the works it cites.

Designing conversational agents for energy feedback

Ulrich Gnewuch, Stefan Morana, Carl Heckmann, and Alexander Maedche · 2018

Later among the works it cites.

How do we model learning at scale? A systematic review of research on MOOCs

Srećko Joksimović, Oleksandra Poquet, Vitomir Kovanović, Nia Dowell, Caitlin Mills, Dragan Gašević, Shane Dawson, Arthur C Graesser, and Christopher Brooks · 2018

Later among the works it cites.

Learning at scale

Ido Roll, Daniel M Russell, and Dragan Gašević · 2018

Later among the works it cites.

Climate change challenges for central banks and financial regulators

Emanuele Campiglio, Yannis Dafermos, Pierre Monnin, Josh Ryan-Collins, Guido Schotten, and Misa Tanaka · 2018

Later among the works it cites.

Designing carbon-neutral investment portfolios

Gianfranco Gianfrate · 2018

Later among the works it cites.

Predicting the carbon price sequence in the shenzhen emissions exchange using a multiscale ensemble forecasting model based on ensemble empirical mode decomposition

Jianguo Zhou, Xuechao Yu, and Xiaolei Yuan · 2018

Later among the works it cites.

Artificial intelligence for social good

Original

Gregory D Hager, Ann Drobnis, Fei Fang, Rayid Ghani, Amy Greenwald, Terah Lyons, David C Parkes, Jason Schultz, Suchi Saria, Stephen F Smith, et al · 2019

Closest in time.

AI for the common good?! pitfalls, challenges, and ethics pen-testing

Bettina Berendt · 2019

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Computational sustainability: Computing for a better world and a sustainable future

Carla Gomes, Thomas Dietterich, Bistra Dilkina, Ermon Stefano, Fei Fang, Alan Farnsworth, Alan Fern, Xioali Fern, Daniel Fink, Douglas Fisher, Alexander Flecker, Daniel Freund, Angela Fuller, John Gregoire, John Hopcroft, Zico Kolter, Warren Powell, Nicole Santov, John Selker, Bart Selman, Daniel Shelcon, David Shmoys, Milind Tambe, Christopher Wood, Weng-Keen Wong, Xiaojian Wu, Steve Kelling, Yexiang Xue, Amulya Yadav, Aziz Yakubu, and Mary Lou Zeeman · 2019

Closest in time.

Challenges and Prospects for Data-Driven Climate Change Mitigation

Lynn Helena Kaack · 2019

Closest in time.

How artificial intelligence will affect the future of energy and climate

David G. Victor · 2019

Closest in time.

Pvnet: A lrcn architecture for spatio-temporal photovoltaic powerforecasting from numerical weather prediction

Original

Johan Mathe, Nina Miolane, Nicolas Sebastien, and Jeremie Lequeux · 2019

Closest in time.

Machine learning for AC optimal power flow

Neel Guha, Zhecheng Wang, Matt Wytock, and Arun Majumdar · 2019

Closest in time.

Online mixed-integer optimization in milliseconds

Original

Dimitris Bertsimas and Bartolomeo Stellato · 2019

Closest in time.

Learning optimal solutions for extremely fast ac optimal power flow

Original

Ahmed Zamzam and Kyri Baker · 2019

Closest in time.

Meta-optimization of optimal power flow

Mahdi Jamei, Letif Mones, Alex Robson, Lyndon White, James Requeima, and Cozmin Ududec · 2019

Closest in time.

Dynamic energy management

Original

Nicholas Moehle, Enzo Busseti, Stephen Boyd, and Matt Wytock · 2019

Closest in time.

Towards distributed energy services: Decentralizing optimal power flow with machine learning

Original

Roel Dobbe, Oscar Sondermeijer, David Fridovich-Keil, Daniel Arnold, Duncan Callaway, and Claire Tomlin · 2019

Closest in time.

Data-driven control design schemes in active distribution grids: Capabilities and challenges

Stavros Karagiannopoulos, Roel Dobbe, Petros Aristidou, Duncan Callaway, and Gabriela Hug · 2019

Closest in time.

Data-driven local control design for active distribution grids using off-line optimal power flow and machine learning techniques

Stavros Karagiannopoulos, Petros Aristidou, and Gabriela Hug · 2019

Closest in time.

https://camus.energy/ , 2019

Camus Energy · 2019

Closest in time.

https://powertac.org/ , 2019

Powertac · 2019

Closest in time.

Crystal: a multi-agent ai system for automated mapping of materials’ crystal structures

Carla P Gomes, Junwen Bai, Yexiang Xue, Johan Björck, Brendan Rappazzo, Sebastian Ament, Richard Bernstein, Shufeng Kong, Santosh K Suram, R Bruce van Dover, et al · 2019

Closest in time.

Analyzing machine learning models to accelerate generation of fundamental materials insights

Mitsutaro Umehara, Helge S Stein, Dan Guevarra, Paul F Newhouse, David A Boyd, and John M Gregoire · 2019

Closest in time.

Predicting disruptive instabilities in controlled fusion plasmas through deep learning

Julian Kates-Harbeck, Alexey Svyatkovskiy, and William Tang · 2019

Closest in time.

https://www.watttime.org/ , 2019

WattTime · 2019

Closest in time.

https://www.electricitymap.org , 2019

electricitymap · 2019

Closest in time.

https://carbonintensity.org.uk/ , 2019

Carbon intensity api · 2019

Closest in time.

https://www.carbontracker.org/carbon-tracker-to-measure-worlds-power-plant-emissions-from-space-with-support-from-google-org/ , May 2019

Carbon tracker to measure world’s power plant emissions from space with support from google.org · 2019

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Truck traffic monitoring with satellite images

Lynn H. Kaack, George H. Chen, and M. Granger Morgan · 2019

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On-demand motorcycle taxis improve mobility, not sustainability

Anissa Yuniashaesa Suatmadi, Felix Creutzig, and Ilona Otto · 2019

Closest in time.

Material efficiency strategies to reducing greenhouse gas emissions associated with buildings, vehicles, and electronics—a review

Edgar G Hertwich, Saleem Ali, Luca Ciacci, Tomer Fishman, Niko Heeren, Eric Masanet, Farnaz Nojavan Asghari, Elsa Olivetti, Stefan Pauliuk, Qingshi Tu, and Paul Wolfram · 2019

Closest in time.

The roles of users in electric, shared and automated mobility transitions

Jonn Axsen and Benjamin K. Sovacool · 2019

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On the future of transportation in an era of automated and autonomous vehicles

P. A. Hancock, Illah Nourbakhsh, and Jack Stewart · 2019

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Robots in space: Sharing our world with autonomous delivery vehicles

Mason Marks · 2019

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Electric vehicle load disaggregation based on limited activation matching pursuits

Shuangyuan Wang, Ran Li, Adrian Evans, and Furong Li · 2019

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Reinforcement learning for demand response: A review of algorithms and modeling techniques

José Vázquez-Canteli and Zoltán Nagy · 2019

Closest in time.

Data-driven prediction of battery cycle life before capacity degradation

Kristen A Severson, Peter M Attia, Norman Jin, Nicholas Perkins, Benben Jiang, Zi Yang, Michael H Chen, Muratahan Aykol, Patrick K Herring, Dimitrios Fraggedakis, et al · 2019

Closest in time.

Data-driven studies of li-ion-battery materials

Steven K Kauwe, Trevor David Rhone, and Taylor D Sparks · 2019

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Analysis of thousands of electrochemical impedance spectra of lithium-ion cells through a machine learning inverse model

Samuel Buteau and J R. Dahn · 2019

Closest in time.

Governing micro-mobility: A nationwide assessment of electric scooter regulations

Kirstin Anderson-Hall, Brandon Bordenkircher, Riley O’Neil, and Smith C Scott · 2019

Closest in time.

The race to code the curb

Andrew Small and Laura Bliss · 2019

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A two-stage forecasting approach for short-term intermodal freight prediction

José Antonio Moscoso-López, Ignacio Turias, Maria Jesús Jiménez-Come, Juan Jesús Ruiz-Aguilar, and María del Mar Cerbán · 2019

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Exploring the diffusion of low-energy houses: An empirical study in the european union

Mark Olsthoorn, Joachim Schleich, and Corinne Faure · 2019

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Lightlearn: An adaptive and occupant centered controller for lighting based on reinforcement learning

June Young Park, Thomas Dougherty, Hagen Fritz, and Zoltan Nagy · 2019

Closest in time.

Unsupervised wifi-enabled iot device-user association for personalized location-based service

Han Zou, Yuxun Zhou, Jianfei Yang, and Costas J Spanos · 2019

Closest in time.

Intelligent edge computing for IoT-based energy management in smart cities

Yi Liu, Chao Yang, Li Jiang, Shengli Xie, and Yan Zhang · 2019

Closest in time.

Internet of Things: Energy boon or bane?

Eric Hittinger and Paulina Jaramillo · 2019

Closest in time.

Multi-parametric analysis of reliability and energy consumption in IoT: A deep learning approach

Muhammad Ateeq, Farruh Ishmanov, Muhammad Khalil Afzal, and Muhammad Naeem · 2019

Closest in time.

Data colonialism: rethinking big data’s relation to the contemporary subject

Nick Couldry and Ulises A Mejias · 2019

Closest in time.

Grading buildings on energy performance using city benchmarking data

Sokratis Papadopoulos and Constantine E. Kontokosta · 2019

Closest in time.

Leveraging Digitalization for Sustainability in Urban Transport (in print)

Felix Creutzig, Martina Franzen, Rolf Moeckel, Dirk Heinrichs, Kai Nagel, and Helga Weisz · 2019

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Intelligent and energy-efficient data prioritization in green smart cities: Current challenges and future directions

Khan Muhammad, Jaime Lloret, and Sung Wook Baik · 2019

Closest in time.

Smart energy systems for sustainable smart cities: Current developments, trends and future directions

Edward O’Dwyer, Indranil Pan, Salvador Acha, and Nilay Shah · 2019

Closest in time.

Learning about urban climate solutions from case studies

William F Lamb, Felix Creutzig, Max W Callaghan, and Jan C Minx · 2019

Closest in time.

A survey of machine learning techniques for food sales prediction

Grigorios Tsoumakas · 2019

Closest in time.

Accelerated discovery of sustainable building materials

Original

Xiou Ge, Richard T Goodwin, Jeremy R Gregory, Randolph E Kirchain, Joana Maria, and Lav R Varshney · 2019

Closest in time.

Artificial neural network control of thermoelectrically-cooled microfluidics using computer vision based on ir thermography

Benjamin A Rizkin, Karina Popovich, and Ryan L Hartman · 2019

Closest in time.

A graph-convolutional neural network model for the prediction of chemical reactivity

Connor W Coley, Wengong Jin, Luke Rogers, Timothy F Jamison, Tommi S Jaakkola, William H Green, Regina Barzilay, and Klavs F Jensen · 2019

Closest in time.

Who profits from industry 4.0? theory and evidence from the automotive industry

Susan Helper, Raphael Martins, and Robert Seamans · 2019

Closest in time.

Factory records: GE providing Procter & Gamble greater access to the cloud for analyzing manufacturing data, 2019

Brendan Coffey · 2019

Closest in time.

The study of Earth as an integrated system

Nasa Science · 2019

Closest in time.

Ladybird Cobbitty 2017 Brassica Dataset

Asher Bender, Brett Whelan, and Salah Sukkarieh · 2019

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An interpretable produce price forecasting system for small and marginal farmers in india using collaborative filtering and adaptive nearest neighbors

Wei Ma, Kendall Nowocin, Niraj Marathe, and George H Chen · 2019

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Deep learning techniques for agronomy applications

Chi-Hua Chen, Hsu-Yang Kung, and Feng-Jang Hwang · 2019

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Developing the world’s first indicator of forest carbon stocks & emissions

Tara O’Shea · 2019

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The global tree restoration potential

Jean-Francois Bastin, Yelena Finegold, Claude Garcia, Danilo Mollicone, Marcelo Rezende, Devin Routh, Constantin M. Zohner, and Thomas W. Crowther · 2019

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Forest drought resistance at large geographic scales

PG Brodrick, LDL Anderegg, and GP Asner · 2019

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A machine learning approach to map tropical selective logging

Matthew G Hethcoat, David P Edwards, Joao MB Carreiras, Robert G Bryant, Filipe M Franca, and Shaun Quegan · 2019

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Negative Emissions Technologies and Reliable Sequestration: A Research Agenda

Ocean Studies Board, Engineering National Academies of Sciences, Medicine, et al · 2019

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The mutual dependence of negative emission technologies and energy systems

Felix Creutzig, Christian Breyer, Jerome Hilaire, Jan Minx, Glen Peters, and Robert H Socolow · 2019

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Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media

Shaoxing Mo, Yinhao Zhu, Nicholas Zabaras, Xiaoqing Shi, and Jichun Wu · 2019

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Intelligent systems for geosciences: An essential research agenda

Y Gil, S. Pierce, Hassan Babaie, Arindam Banerjee, Kirk Borne, Gary Bust, Michelle Cheatham, Imme Ebert-Uphoff, Carla Gomes, Mary Hill, John Horel, Leslie Hsu, Jim Kinter, Craig Knoblock, David Krum, Vipin Kumar, Pierre Lermusiaux, Yan Liu, Chris North, Victor Pankratius, Shanan Peters, Beth Plale, Allen Pope, Sai Ravela, Juan Restrepo, Aaron Ridley, Hanan Samet, and Shashi Shekhar · 2019

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EnviroNet: ImageNet for environment

Surya Karthik Mukkavilli · 2019

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Deep learning and process understanding for data-driven earth system science

Markus Reichstein, Gustau Camps-Valls, Bjorn Stevens, Martin Jung, Joachim Denzler, Nuno Carvalhais, and Prabhat · 2019

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Improving subseasonal forecasting in the western U.S. with machine learning

Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, and Lester Mackey · 2019

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Evaluation of machine learning algorithms in spatial downscaling of MODIS land surface temperature

Wan Li, Li Ni, Zhao-liang Li, Si-bo Duan, and Hua Wu · 2019

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Decentralized flood forecasting using deep neural networks

Original

Muhammed Sit and Ibrahim Demir · 2019

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Synthetic examples improve generalization for rare classes

Original

Sara Beery, Yang Liu, Dan Morris, Jim Piavis, Ashish Kapoor, Markus Meister, and Pietro Perona · 2019

Closest in time.

Bias reduction via end-to-end shift learning: Application to citizen science

Di Chen and Carla P Gomes · 2019

Closest in time.

Machine learning approaches for anomaly detection of water quality on a real-world data set

Fitore Muharemi, Doina Logofătu, and Florin Leon · 2019

Closest in time.

Learning about climate change uncertainty enables flexible water infrastructure planning

Sarah Fletcher, Megan Lickley, and Kenneth Strzepek · 2019

Closest in time.

Institute for Water Education website

The water, peace and security partnership · 2019

Closest in time.

Physics-guided data science for food security and climate

Venkata Shashank Konduri, Jitendra Kumar, Forrest Hoffman, Udit Bhatia, Tarik Gouthier, and Auroop Ganguly · 2019

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Agriculture commodity arrival prediction using remote sensing data: Insights and beyond

Gautam Prasad, Upendra Reddy Vuyyuru, and Mithun Das Gupta · 2019

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Comparison of machine learning algorithms for retrieval of water quality indicators in case-II waters: a case study of Hong Kong

Sidrah Hafeez, Man Sing Wong, Hung Chak Ho, Majid Nazeer, Janet Nichol, Sawaid Abbas, Danling Tang, Kwon Ho Lee, and Lilian Pun · 2019

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Creating xBD: A dataset for assessing building damage from satellite imagery

Ritwik Gupta, Bryce Goodman, Nirav Patel, Ricky Hosfelt, Sandra Sajeev, Eric Heim, Jigar Doshi, Keane Lucas, Howie Choset, and Matthew Gaston · 2019

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Halving warming with idealized solar geoengineering moderates key climate hazards

Peter Irvine, Kerry Emanuel, Jie He, Larry W Horowitz, Gabriel Vecchi, and David Keith · 2019

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A process study on thinning of arctic winter cirrus clouds with high-resolution icon-art simulations

Simon Gruber, Ulrich Blahak, Florian Haenel, Christoph Kottmeier, Thomas Leisner, Harel Muskatel, Trude Storelvmo, and Bernhard Vogel · 2019

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Stratospheric aerosol injection as a deep reinforcement learning problem

Original

Christian Schroeder de Witt and Thomas Hornigold · 2019

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Global warming has increased global economic inequality

Noah S Diffenbaugh and Marshall Burke · 2019

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Commitment failures are unlikely to undermine public support for the paris agreement

Liam F Beiser-McGrath and Thomas Bernauer · 2019

Closest in time.

Visualizing the consequences of climate change using cycle-consistent adversarial networks

Original

Victor Schmidt, Alexandra Luccioni, S Karthik Mukkavilli, Narmada Balasooriya, Kris Sankaran, Jennifer Chayes, and Yoshua Bengio · 2019

Closest in time.

A deep learning and gamification approach to improving human-building interaction and energy efficiency in smart infrastructure

Ioannis C Konstantakopoulos, Andrew R Barkan, Shiying He, Tanya Veeravalli, Huihan Liu, and Costas Spanos · 2019

Closest in time.

Empirically grounded agent-based models of innovation diffusion: a critical review

Haifeng Zhang and Yevgeniy Vorobeychik · 2019

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Improved cooperative multi-agent reinforcement learning algorithm augmented by mixing demonstrations from centralized policy

Hyun-Rok Lee and Taesik Lee · 2019

Closest in time.

Policy design for the anthropocene

Thomas Sterner, Edward B. Barbier, Ian Bateman, Inge van den Bijgaart, Anne-Sophie Crépin, Ottmar Edenhofer, Carolyn Fischer, Wolfgang Habla, John Hassler, Olof Johansson-Stenman, Andreas Lange, Stephen Polasky, Johan Rockström, Henrik G. Smith, Will Steffen, Gernot Wagner, James E. Wilen, Francisco Alpízar, Christian Azar, Donna Carless, Carlos Chávez, Jessica Coria, Gustav Engström, Sverker C. Jagers, Gunnar Köhlin, Åsa Löfgren, Håkan Pleijel, and Amanda Robinson · 2019

Closest in time.

Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning

Christian Folberth, Artem Baklanov, Juraj Balkovič, Rastislav Skalskỳ, Nikolay Khabarov, and Michael Obersteiner · 2019

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Geographically weighted machine learning and downscaling for high-resolution spatiotemporal estimations of wind speed

Lianfa Li · 2019

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Evaluation of machine learning algorithms in spatial downscaling of modis land surface temperature

Wan Li, Li Ni, Zhao-Liang Li, Si-Bo Duan, and Hua Wu · 2019

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Machine learning for high-dimensional dynamic stochastic economies

Simon Scheidegger and Ilias Bilionis · 2019

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Efficient multi-objective optimization through population-based parallel surrogate search

Original

Taimoor Akhtar and Christine A Shoemaker · 2019

Closest in time.

The seven tools of causal inference, with reflections on machine learning

Judea Pearl · 2019

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Machine learning methods that economists should know about

Susan Athey and Guido W Imbens · 2019

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A second chance to get causal inference right: A classification of data science tasks

Miguel A. Hernán, John Hsu, and Brian Healy · 2019

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Machine learning in policy evaluation: new tools for causal inference, 2019

Noemi Kreif and Karla DiazOrdaz · 2019

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On the use of machine learning for causal inference in climate economics

Isabel Hovdahl · 2019

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Machine learning in energy economics and finance: A review

Hamed Ghoddusi, Germán G Creamer, and Nima Rafizadeh · 2019

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Techno-economic optimization and social costs assessment of microgrid-conventional grid integration using genetic algorithm and artificial neural networks: A case study for two US cities

Prashant Nagapurkar and Joseph D Smith · 2019

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Research on optimization allocation scheme of initial carbon emission quota from the perspective of welfare effect

Qunli Wu and Hongjie Zhang · 2019

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Climate change and educational attainment in the global tropics

Heather Randell and Clark Gray · 2019

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Hedging climate change news

Robert F Engle, Stefano Giglio, Heebum Lee, Bryan T Kelly, and Johannes Stroebel · 2019

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Machine vision for natural gas methane emissions detection using an infrared camera

Jingfan Wang, Lyne P. Tchapmi, Arvind P. Ravikumar, Mike McGuire, Clay S. Bell, Daniel Zimmerle, Silvio Savarese, and Adam R. Brandt · 2020

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