4 papers · 1 filter
Frequency-Separable Hamiltonian Neural Network for Multi-Timescale Dynamics
Yaojun Li, Yulong Yang, Christine Allen-Blanchette
While Hamiltonian mechanics provides a powerful inductive bias for neural networks modeling dynamical systems, Hamiltonian Neural Networks and their variants often fail to capture…
Discovering Phase Space Structure in Learned Hamiltonian Systems
Jiayin Liu, Yulong Yang, Vineet Bansal +1
Mechanics-inspired neural dynamical models improve interpretability and physical consistency, but they usually assume a known configuration space, fixed physical parameters, and de…
Resolving Oversmoothing with Opinion Dissensus
Keqin Wang, Yulong Yang, Ishan Saha +1
While graph neural networks (GNNs) have allowed researchers to successfully apply neural networks to non-Euclidean domains, deep GNNs often exhibit lower predictive performance tha…
Behavior-Inspired Neural Networks for Relational Inference
Yulong Yang, Bowen Feng, Keqin Wang +3
From pedestrians to Kuramoto oscillators, interactions between agents govern how dynamical systems evolve in space and time. Discovering how these agents relate to each other has t…