1 citations · 1 across the 4 of their papers we have counts for
4 papers
Towards Principled Test-Time Adaptation for Time Series Forecasting
Haochun Wang, Ruichen Xu, Georgios Kementzidis +3
Test-time adaptation (TTA) has recently emerged as a promising approach for improving time series forecasting (TSF) under distribution shift. Existing TSF-TTA methods differ in how…
Kolmogorov-Arnold Representation for Symplectic Learning: Advancing Hamiltonian Neural Networks
Zongyu Wu, Ruichen Xu, Luoyao Chen +3
We propose a Kolmogorov-Arnold Representation-based Hamiltonian Neural Network (KAR-HNN) that replaces the Multilayer Perceptrons (MLPs) with univariate transformations. While Hami…
An Iterative Framework for Generative Backmapping of Coarse Grained Proteins
Georgios Kementzidis, Erin Wong, John Nicholson +2
The techniques of data-driven backmapping from coarse-grained (CG) to fine-grained (FG) representation often struggle with accuracy, unstable training, and physical realism, especi…
Velocity-Inferred Hamiltonian Neural Networks: Learning Energy-Conserving Dynamics from Position-Only Data
Ruichen Xu, Zongyu Wu, Luoyao Chen +5
Data-driven modeling of physical systems often relies on learning both positions and momenta to accurately capture Hamiltonian dynamics. However, in many practical scenarios, only…