ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method

Combining crowd-sourcing and deep learning to explore the meso-scale organization of shallow convection

Original

Stephan Rasp, Hauke Schulz, Sandrine Bony, and Bjorn Stevens. 2020b · 1906

Earlier work this paper cites.

Limiting forms of the frequency distribution of the largest or smallest member of a sample. In Mathematical proceedings of the Cambridge philosophical society , Vol. 24. Cambridge University Press, 180–190

Ronald Aylmer Fisher and Leonard Henry Caleb Tippett. 1928 · 1928

Earlier work this paper cites.

The general circulation of the atmosphere: A numerical experiment

Norman A Phillips. 1956 · 1956

Earlier work this paper cites.

Investigating causal relations by econometric models and cross-spectral methods

Clive WJ Granger. 1969 · 1969

Earlier work this paper cites.

Statistics of extremes: theory and applications . Vol. 558

Jan Beirlant, Yuri Goegebeur, Johan Segers, and Jozef L Teugels. 2004 · 2004

Earlier work this paper cites.

Temporal causal modeling with graphical granger methods. In Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, California, USA, August 12-15, 2007 , Pavel Berkhin, Rich Caruana, and Xindong Wu (Eds.). ACM, 66–75

Andrew Arnold, Yan Liu, and Naoki Abe. 2007 · 2007

Earlier work this paper cites.

The origins of computer weather prediction and climate modeling

Peter Lynch. 2008 · 2008

Earlier work this paper cites.

FlowDB a large scale precipitation, river, and flash flood dataset

Original

Isaac Godfried, Kriti Mahajan, Maggie Wang, Kevin Li, and Pranjalya Tiwari. 2020 · 2012

Earlier work this paper cites.

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Original

Junyoung Chung, Çaglar Gülçehre, KyungHyun Cho, and Yoshua Bengio. 2014 · 2014

Earlier work this paper cites.

Auto-Encoding Variational Bayes. In 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Conference Track Proceedings , Yoshua Bengio and Yann LeCun (Eds.)

Original

Diederik P. Kingma and Max Welling. 2014 · 2014

Earlier work this paper cites.

Sequence to Sequence Learning with Neural Networks. In Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada , Zoubin Ghahramani, Max Welling, Corinna Cortes, Neil D. Lawrence, and Kilian Q. Weinberger (Eds.). 3104–3112

Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014 · 2014

Earlier work this paper cites.

Variational Graph Auto-Encoders

Original

Thomas N. Kipf and Max Welling. 2016 · 2016

Earlier work this paper cites.

Rethinking atrous convolution for semantic image segmentation

Original

Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam. 2017 · 2017

Earlier work this paper cites.

Categorical Reparameterization with Gumbel-Softmax. In 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings . OpenReview.net

Eric Jang, Shixiang Gu, and Ben Poole. 2017 · 2017

Earlier work this paper cites.

The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables. In 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings . OpenReview.net

Chris J. Maddison, Andriy Mnih, and Yee Whye Teh. 2017 · 2017

Earlier work this paper cites.

ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA , Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, and Roman Garnett (Eds.). 3402–3413

Evan Racah, Christopher Beckham, Tegan Maharaj, Samira Ebrahimi Kahou, Prabhat, and Chris Pal. 2017 · 2017

Earlier work this paper cites.

Anomaly Detection in Streams with Extreme Value Theory. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13 - 17, 2017 . ACM, 1067–1075

Alban Siffer, Pierre-Alain Fouque, Alexandre Termier, and Christine Largouët. 2017 · 2017

Earlier work this paper cites.

ERA5 hourly data on single levels from 1979 to present

Hans Hersbach, Bill Bell, Paul Berrisford, Gionata Biavati, András Horányi, Joaquín Muñoz Sabater, Julien Nicolas, Carole Peubey, Raluca Radu, Iryna Rozum, et al · 2018

Earlier work this paper cites.

Neural Relational Inference for Interacting Systems. In Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018 (Proceedings of Machine Learning Research, Vol. 80) , Jennifer G. Dy and Andreas Krause (Eds.). PMLR, 2693–2702

Thomas N. Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, and Richard S. Zemel. 2018 · 2018

Earlier work this paper cites.

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. In 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings . OpenReview.net

Yaguang Li, Rose Yu, Cyrus Shahabi, and Yan Liu. 2018 · 2018

Earlier work this paper cites.

Deep One-Class Classification. In Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018 (Proceedings of Machine Learning Research, Vol. 80) , Jennifer G. Dy and Andreas Krause (Eds.). PMLR, 4390–4399

Lukas Ruff, Nico Görnitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Robert A. Vandermeulen, Alexander Binder, Emmanuel Müller, and Marius Kloft. 2018 · 2018

Earlier work this paper cites.

DAGs with NO TEARS: Continuous Optimization for Structure Learning. In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada , Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, and Roman Garnett (Eds.). 9492–9503

Xun Zheng, Bryon Aragam, Pradeep Ravikumar, and Eric P. Xing. 2018 · 2018

Earlier work this paper cites.

Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019 , Ankur Teredesai, Vipin Kumar, Ying Li, Rómer Rosales, Evimaria Terzi, and George Karypis (Eds.). ACM, 2828–2837

Ya Su, Youjian Zhao, Chenhao Niu, Rong Liu, Wei Sun, and Dan Pei. 2019 · 2019

Earlier work this paper cites.

DAG-GNN: DAG Structure Learning with Graph Neural Networks. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA (Proceedings of Machine Learning Research, Vol. 97) , Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, 7154–7163

Yue Yu, Jie Chen, Tian Gao, and Mo Yu. 2019 · 2019

Earlier work this paper cites.

Deep Multimodality Model for Multi-task Multi-view Learning. In Proceedings of the 2019 SIAM International Conference on Data Mining, SDM 2019, Calgary, Alberta, Canada, May 2-4, 2019 , Tanya Y. Berger-Wolf and Nitesh V. Chawla (Eds.). SIAM, 10–18

Lecheng Zheng, Yu Cheng, and Jingrui He. 2019 · 2019

Earlier work this paper cites.

TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting

Gabriele Franch, Valerio Maggio, Luca Coviello, Marta Pendesini, Giuseppe Jurman, and Cesare Furlanello. 2020 · 2020

Earlier work this paper cites.

DROCC: Deep Robust One-Class Classification. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event (Proceedings of Machine Learning Research, Vol. 119) . PMLR, 3711–3721

Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, and Prateek Jain. 2020 · 2020

Earlier work this paper cites.

Transductive LSTM for time-series prediction: An application to weather forecasting

Zahra Karevan and Johan AK Suykens. 2020 · 2020

Earlier work this paper cites.

Deepti: Deep-Learning-Based Tropical Cyclone Intensity Estimation System

Manil Maskey, Rahul Ramachandran, Muthukumaran Ramasubramanian, Iksha Gurung, Brian Freitag, Aaron Kaulfus, Drew Bollinger, Daniel J. Cecil, and Jeffrey J. Miller. 2020 · 2020

Earlier work this paper cites.

WeatherBench: a benchmark data set for data-driven weather forecasting

Stephan Rasp, Peter D Dueben, Sebastian Scher, Jonathan A Weyn, Soukayna Mouatadid, and Nils Thuerey. 2020a · 2020

Earlier work this paper cites.

Deep Semi-Supervised Anomaly Detection. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020 . OpenReview.net

Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, and Marius Kloft. 2020 · 2020

Earlier work this paper cites.

RainBench: Enabling Data-Driven Precipitation Forecasting on a Global Scale. In NeurIPS 2020 Workshop on Tackling Climate Change with Machine Learning

Catherine Tong, Christian A Schroeder de Witt, Valentina Zantedeschi, Daniele De Martini, Alfredo Kalaitzis, Matthew Chantry, Duncan Watson-Parris, and Piotr Bilinski. 2020 · 2020

Earlier work this paper cites.

A Comprehensive Survey on Graph Neural Networks

Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and Philip S. Yu. 2021 · 2020

Earlier work this paper cites.

MMSegmenation

Jiarui Xu, Kai Chen, and Dahua Lin. 2020 · 2020

Cited alongside, same era.

Multivariate Time-series Anomaly Detection via Graph Attention Network. In 20th IEEE International Conference on Data Mining, ICDM 2020, Sorrento, Italy, November 17-20, 2020 , Claudia Plant, Haixun Wang, Alfredo Cuzzocrea, Carlo Zaniolo, and Xindong Wu (Eds.). IEEE, 841–850

Hang Zhao, Yujing Wang, Juanyong Duan, Congrui Huang, Defu Cao, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, and Qi Zhang. 2020 · 2020

Cited alongside, same era.

Domain Adaptive Multi-Modality Neural Attention Network for Financial Forecasting. In WWW ’20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020 , Yennun Huang, Irwin King, Tie-Yan Liu, and Maarten van Steen (Eds.). ACM / IW3C2, 2230–2240

Dawei Zhou, Lecheng Zheng, Yada Zhu, Jianbo Li, and Jingrui He. 2020 · 2020

Cited alongside, same era.

AQ-Bench: a benchmark dataset for machine learning on global air quality metrics

Clara Betancourt, Timo Stomberg, Ribana Roscher, Martin G Schultz, and Scarlet Stadtler. 2021 · 2021

Cited alongside, same era.

Learning skillful medium-range global weather forecasting

Remi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Ferran Alet, Suman Ravuri, Timo Ewalds, Zach Eaton-Rosen, Weihua Hu, et al · 2023

Later among the works it cites.

SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 , Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, and Sergey Levine (Eds.)

Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, and Lester Mackey. 2023 · 2023

Later among the works it cites.

ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 , Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, and Sergey Levine (Eds.)

Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, and Aditya Grover. 2023 · 2023

Later among the works it cites.