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cs.LG2026
Smoothness Errors in Dynamics Models and How to Avoid Them
Edward Berman, Luisa Li, Jung Yeon Park +1
Modern neural networks have shown promise for solving partial differential equations over surfaces, often by discretizing the surface as a mesh and learning with a mesh-aware graph…
cs.LG2024
Approximate Equivariance in Reinforcement Learning
Jung Yeon Park, Sujay Bhatt, Sihan Zeng +4
Equivariant neural networks have shown great success in reinforcement learning, improving sample efficiency and generalization when there is symmetry in the task. However, in many…
cs.LG2023
Modeling Dynamics over Meshes with Gauge Equivariant Nonlinear Message Passing
Jung Yeon Park, Lawson L. S. Wong, Robin Walters
Data over non-Euclidean manifolds, often discretized as surface meshes, naturally arise in computer graphics and biological and physical systems. In particular, solutions to partia…