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cs.LG2026
Training Without Orthogonalization, Inference With SVD: A Gradient Analysis of Rotation Representations
Chris Choy
Recent work has shown that removing orthogonalization during training and applying it only at inference improves rotation estimation in deep learning, with empirical evidence favor…
cs.LG2024
Exploring the design space of deep-learning-based weather forecasting systems
Shoaib Ahmed Siddiqui, Jean Kossaifi, Boris Bonev +4
Despite tremendous progress in developing deep-learning-based weather forecasting systems, their design space, including the impact of different design choices, is yet to be well u…
cs.LG2023★ 31 cited
Geometry-Informed Neural Operator for Large-Scale 3D PDEs
Zongyi Li, Nikola Borislavov Kovachki, Chris Choy +8
We propose the geometry-informed neural operator (GINO), a highly efficient approach to learning the solution operator of large-scale partial differential equations with varying ge…