3 papers
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.CV2025
Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction
Chris Choy, Alexey Kamenev, Jean Kossaifi +3
Computational Fluid Dynamics (CFD) is crucial for automotive design, requiring the analysis of large 3D point clouds to study how vehicle geometry affects pressure fields and drag…
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…