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Crop management plays a crucial role in determining crop yield, economic profitability, and environmental sustainability.
Using extended machine learning and simulation technics to design crop management strategies
J-M Attonaty, M-H Chatelin, F Garcia, and S Ndiaye · 1997
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Use of reinforcement learning and simulation to optimize wheat crop technical management
Frédérick Garcia · 1999
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Nitrate leaching in temperate agroecosystems: sources, factors and mitigating strategies
HJ Di and KC Cameron · 2002
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The DSSAT cropping system model
James W Jones, Gerrit Hoogenboom, Cheryl H Porter, Ken J Boote, William D Batchelor, LA Hunt, Paul W Wilkens, Upendra Singh, Arjan J Gijsman, and Joe T Ritchie · 2003
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Crop management factors influencing yield and quality of crop residues
BVS Reddy, P Sanjana Reddy, F Bidinger, and Michael Blümmel · 2003
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Forecasting of solar radiation
Detlev Heinemann, Elke Lorenz, and Marco Girodo · 2006
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Why does my soil moisture sensor read negative?
Douglas R Cobos and Decagon Devices · 2010
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Weather forecast accuracy analysis
Eric Floehr · 2010
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Impact of sprinkler irrigation management on the del reguero river (spain). i: Water balance and irrigation performance
Ahmed Skhiri and Farida Dechmi · 2012
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Uncertainty in simulating wheat yields under climate change
Senthold Asseng, Frank Ewert, Cynthia Rosenzweig, James W Jones, Jerry L Hatfield, Alex C Ruane, Kenneth J Boote, Peter J Thorburn, Reimund P Rötter, Davide Cammarano, et al · 2013
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The influence of organic and conventional fertilisation and crop protection practices, preceding crop, harvest year and weather conditions on yield and quality of potato (Solanum tuberosum) in a long-term management trial
Mike W Palmer, Julia Cooper, Catherine Tétard-Jones, et al · 2013
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How do various maize crop models vary in their responses to climate change factors?
Simona Bassu, Nadine Brisson, Jean-Louis Durand, Kenneth Boote, Jon Lizaso, James W Jones, Cynthia Rosenzweig, Alex C Ruane, Myriam Adam, Christian Baron, et al · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, et al · 2015
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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Personalized fall risk assessment for long-term care services improvement
Suiyao Chen, William D Kearns, James L Fozard, and Mingyang Li · 2017
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Brief history of agricultural systems modeling
James W Jones, John M Antle, Bruno Basso, Kenneth J Boote, Richard T Conant, Ian Foster, H Charles J Godfray, Mario Herrero, Richard E Howitt, Sander Janssen, et al · 2017
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Combining incremental conductance and firefly algorithm for tracking the global mpp of pv arrays
Ji-Ying Shi, Le-Tao Ling, Fei Xue, Zi-Jian Qin, Ya-Jing Li, Zhi-Xin Lai, and Ting Yang · 2017
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Reinforcement learning control for water-efficient agricultural irrigation
Lijia Sun, Yanxiang Yang, Jiang Hu, Dana Porter, Thomas Marek, and Charles Hillyer · 2017
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Domain randomization for transferring deep neural networks from simulation to the real world
Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, and Pieter Abbeel · 2017
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A data heterogeneity modeling and quantification approach for field pre-assessment of chloride-induced corrosion in aging infrastructures
Suiyao Chen, Lu Lu, Yisha Xiang, Qing Lu, and Mingyang Li · 2018
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Deep drone racing: Learning agile flight in dynamic environments
Elia Kaufmann, Antonio Loquercio, Rene Ranftl, Alexey Dosovitskiy, Vladlen Koltun, and Davide Scaramuzza · 2018
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Sim-to-real transfer of robotic control with dynamics randomization
Xue Bin Peng, Marcin Andrychowicz, Wojciech Zaremba, and Pieter Abbeel · 2018
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Short-term rainfall forecasting using multi-layer perceptron
Pengcheng Zhang, Yangyang Jia, Jerry Gao, Wei Song, and Hareton Leung · 2018
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Claims data-driven modeling of hospital time-to-readmission risk with latent heterogeneity
Suiyao Chen, Nan Kong, Xuxue Sun, Hongdao Meng, and Mingyang Li · 2019
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Confidence trigger detection: an approach to build real-time tracking-by-detection system
Zhicheng Ding and Edward Wong · 2019
Cited alongside, same era.
Dssat-ceres-maize modelling to improve irrigation and nitrogen management practices under mediterranean conditions
Wafa Malik, Ramon Isla, and Farida Dechmi · 2019
Cited alongside, same era.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf · 2019
Open-vocabulary queryable scene representations for real world planning
Boyuan Chen, Fei Xia, Brian Ichter, Kanishka Rao, Keerthana Gopalakrishnan, Michael S Ryoo, Austin Stone, and Daniel Kappler · 2023
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Jiuhai Chen and Jonas Mueller · 2023
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Safe and efficient reinforcement learning using disturbance-observer-based control barrier functions
Yikun Cheng, Pan Zhao, and Naira Hovakimyan · 2023
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How many validation labels do you need? exploring the design space of label-efficient model ranking
Zhengyu Hu, Jieyu Zhang, Yue Yu, Yuchen Zhuang, and Hui Xiong · 2023
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Nitrogen management with reinforcement learning and crop growth models
Michiel GJ Kallenberg, Hiske Overweg, Ron van Bree, and Ioannis N Athanasiadis · 2023
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Cited alongside, same era.
Creating a sustainable food future: A menu of solutions to feed nearly 10 billion people by 2050. final report
Tim Searchinger, Richard Waite, Craig Hanson, Janet Ranganathan, Patrice Dumas, Emily Matthews, and Carni Klirs · 2019
Cited alongside, same era.
A simple crop model
Chuang Zhao, Bing Liu, Liujun Xiao, Gerrit Hoogenboom, Kenneth J Boote, Belay T Kassie, Willingthon Pavan, Vakhtang Shelia, Kwang Soo Kim, Ixchel M Hernandez-Ochoa, et al · 2019
Cited alongside, same era.
Optimal binomial reliability demonstration tests design under acceptance decision uncertainty
Suiyao Chen, Lu Lu, Qiong Zhang, and Mingyang Li · 2020
Cited alongside, same era.
Sim-to-real transfer in deep reinforcement learning for robotics: a survey
Wenshuai Zhao, Jorge Peña Queralta, and Tomi Westerlund · 2020
Cited alongside, same era.
Application, adoption and opportunities for improving decision support systems in irrigated agriculture: A review
Iffat Ara, Lydia Turner, Matthew Tom Harrison, Marta Monjardino, Peter DeVoil, and Daniel Rodriguez · 2021
Cited alongside, same era.
Machine learning aided crop yield optimization
Chace Ashcraft and Kiran Karra · 2021
Cited alongside, same era.
Cropgym: a reinforcement learning environment for crop management
Hiske Overweg, Herman NC Berghuijs, and Ioannis N Athanasiadis · 2021
Cited alongside, same era.
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Synthetic data generation with large language models for text classification: Potential and limitations
Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, and Ming Yin · 2023
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Code as policies: Language model programs for embodied control
Jacky Liang, Wenlong Huang, Fei Xia, Peng Xu, Karol Hausman, Brian Ichter, Pete Florence, and Andy Zeng · 2023
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Meta inverse constrained reinforcement learning: Convergence guarantee and generalization analysis
Shicheng Liu and Minghui Zhu · 2023
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A swat-based reinforcement learning framework for crop management
Malvern Madondo, Muneeza Azmat, Kelsey Dipietro, Raya Horesh, Michael Jacobs, Arun Bawa, Raghavan Srinivasan, and Fearghal O’Donncha · 2023
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Grounding language with visual affordances over unstructured data
Oier Mees, Jessica Borja-Diaz, and Wolfram Burgard · 2023
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Generative agents: Interactive simulacra of human behavior
Joon Sung Park, Joseph O’Brien, Carrie Jun Cai, Meredith Ringel Morris, Percy Liang, and Michael S Bernstein · 2023
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Emp: emotion-guided multi-modal fusion and contrastive learning for personality traits recognition
Yusong Wang, Dongyuan Li, Kotaro Funakoshi, and Manabu Okumura · 2023
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Mmap: Multi-modal alignment prompt for cross-domain multi-task learning
Yi Xin, Junlong Du, Qiang Wang, Ke Yan, and Shouhong Ding · 2023
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Thread of thought unraveling chaotic contexts
Yucheng Zhou, Xiubo Geng, Tao Shen, Chongyang Tao, Guodong Long, Jian-Guang Lou, and Jianbing Shen · 2023
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Language models can solve computer tasks
Geunwoo Kim, Pierre Baldi, and Stephen McAleer · 2024
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Adaptive ensembles of fine-tuned transformers for llm-generated text detection
Zhixin Lai, Xuesheng Zhang, and Suiyao Chen · 2024
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Learning multi-agent behaviors from distributed and streaming demonstrations
Shicheng Liu and Minghui Zhu · 2024
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Temperature-scaling surprisal estimates improve fit to human reading times–but does it do so for the “right reasons”?
Tong Liu, Iza Škrjanec, and Vera Demberg · 2024
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Reflexion: Language agents with verbal reinforcement learning
Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao · 2024
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Large language models for forecasting and anomaly detection: A systematic literature review
Jing Su, Chufeng Jiang, Xin Jin, Yuxin Qiao, Tingsong Xiao, Hongda Ma, Rong Wei, Zhi Jing, Jiajun Xu, and Junhong Lin · 2024
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Switchtab: Switched autoencoders are effective tabular learners
Jing Wu, Suiyao Chen, Qi Zhao, Renat Sergazinov, Chen Li, Shengjie Liu, Chongchao Zhao, Tianpei Xie, Hanqing Guo, Cheng Ji, et al · 2024
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On the trade-off of intra-/inter-class diversity for supervised pre-training
Jieyu Zhang, Bohan Wang, Zhengyu Hu, Pang Wei W Koh, and Alexander J Ratner · 2024
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Visual in-context learning for large vision-language models
Yucheng Zhou, Xiang Li, Qianning Wang, and Jianbing Shen · 2024
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