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Deep generative models are increasingly used to gain insights in the geospatial data domain, e.g., for climate data.
OpenStreetMap: user-generated street maps
Patrick Weber and Muki Haklay · 2008
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TECA: A parallel toolkit for extreme climate analysis
Prabhat, Oliver Rübel, Surendra Byna, Kesheng Wu, Fuyu Li, Michael Wehner, and Wes Bethel · 2012
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Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Conditional generative adversarial nets, 2014
Mehdi Mirza and Simon Osindero · 2014
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Forecasting the weather of nevada: A deep learning approach
Moinul Hossain, Banafsheh Rekabdar, Sushil J Louis, and Sergiu Dascalu · 2015
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A short-term rainfall prediction model using multi-task convolutional neural networks
Minghui Qiu, Peilin Zhao, Ke Zhang, Jun Huang, Xing Shi, Xiaoguang Wang, and Wei Chu · 2017
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Extremeweather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events
Evan Racah, Christopher Beckham, Tegan Maharaj, Samira Ebrahimi Kahou, Mr Prabhat, and Chris Pal · 2017
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Lip movements generation at a glance
Lele Chen, Zhiheng Li, Ross K Maddox, Zhiyao Duan, and Chenliang Xu · 2018
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Spatio-temporal stacked lstm for temperature prediction in weather forecasting
Zahra Karevan and Johan AK Suykens · 2018
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Toward data-driven weather and climate forecasting: Approximating a simple general circulation model with deep learning
Sebastian Scher · 2018
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Learning to generate time-lapse videos using multi-stage dynamic generative adversarial networks
Wei Xiong, Wenhan Luo, Lin Ma, Wei Liu, and Jiebo Luo · 2018
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Adversarial video generation on complex datasets
Aidan Clark, Jeff Donahue, and Karen Simonyan · 2019
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Neural rendering and reenactment of human actor videos
Lingjie Liu, Weipeng Xu, Michael Zollhoefer, Hyeongwoo Kim, Florian Bernard, Marc Habermann, Wenping Wang, and Christian Theobalt · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Spatial interpolation using conditional generative adversarial neural networks
Di Zhu, Ximeng Cheng, Fan Zhang, Xin Yao, Yong Gao, and Yu Liu · 2019
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Multisensor data fusion for cloud removal in global and all-season sentinel-2 imagery
Patrick Ebel, Andrea Meraner, Michael Schmitt, and Xiao Xiang Zhu · 2020
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Artificial intelligence reconstructs missing climate information
Christopher Kadow, David Matthew Hall, and Uwe Ulbrich · 2020
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Sxl: Spatially explicit learning of geographic processes with auxiliary tasks
Konstantin Klemmer and Daniel B Neill · 2020
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Change detection in image time-series using unsupervised lstm
Sudipan Saha, Francesca Bovolo, and Lorenzo Bruzzone · 2020
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Tackling climate change with machine learning
David Rolnick, Priya L Donti, Lynn H Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, et al · 2019
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Gencer Sumbul, Marcela Charfuelan, Begüm Demir, and Volker Markl · 2019
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Cot-gan: Generating sequential data via causal optimal transport
Tianlin Xu, Li K Wenliang, Michael Munn, and Beatrice Acciaio · 2020
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Physics-informed semantic inpainting: Application to geostatistical modeling
Qiang Zheng, Lingzao Zeng, and George Em Karniadakis · 2020
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Gustau Camps-Valls, Devis Tuia, Xiao Xiang Zhu, and Markus Reichstein (Editors) · 2021
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