81 citations · 181 across the 14 of their papers we have counts for
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cs.LG2022★ 6 cited
Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts
Rui Wang, Yihe Dong, Sercan Ö. Arik +1
Temporal distributional shifts, with underlying dynamics changing over time, frequently occur in real-world time series and pose a fundamental challenge for deep neural networks (D…
cs.LG2022★ 5 cited
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting
Rui Wang, Robin Walters, Rose Yu
Exploiting symmetry in dynamical systems is a powerful way to improve the generalization of deep learning. The model learns to be invariant to transformation and hence is more robu…
cs.LG2022★ 11 cited
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics
Rui Wang, Robin Walters, Rose Yu
Incorporating symmetry as an inductive bias into neural network architecture has led to improvements in generalization, data efficiency, and physical consistency in dynamics modeli…