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ORCIDVenkatesh Ramesh
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2020 – today
- 2024
[i5]Venkatesh Ramesh, Arthur Ouaknine, David Rolnick:
Tree semantic segmentation from aerial image time series. CoRR abs/2407.13102 (2024)- 2023
- [j1]Paula Harder, Alex Hernández-García, Venkatesh Ramesh, Qidong Yang, Prasanna Sattegeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick:
Hard-Constrained Deep Learning for Climate Downscaling. J. Mach. Learn. Res. 24: 365:1-365:40 (2023) - [c2]Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick:
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. NeurIPS 2023 - [i4]Qidong Yang, Alex Hernández-García, Paula Harder, Venkatesh Ramesh, Prasanna Sattigeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick:
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling. CoRR abs/2305.14452 (2023) - [i3]Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick:
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. CoRR abs/2311.03721 (2023) - 2022
- [i2]Paula Harder, Qidong Yang, Venkatesh Ramesh, Prasanna Sattigeri, Alex Hernández-García, Campbell D. Watson, Daniela Szwarcman, David S. Rolnick
:
Generating physically-consistent high-resolution climate data with hard-constrained neural networks. CoRR abs/2208.05424 (2022) - 2021
- [c1]Salva Rühling Cachay, Venkatesh Ramesh, Jason N. S. Cole, Howard Barker, David Rolnick:
ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models. NeurIPS Datasets and Benchmarks 2021 - [i1]Salva Rühling Cachay, Venkatesh Ramesh, Jason N. S. Cole, Howard Barker, David Rolnick:
ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models. CoRR abs/2111.14671 (2021)
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