4 citations · 7 across the 7 of their papers we have counts for
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cs.LG2025
KITINet: KInetic Theory Inspired Inter-Channel Information Exchange for Residual Networks
Mingquan Feng, Yifan Fu, Tongcheng Zhang +3
Residual connections are foundational to modern neural networks, yet the standard additive update provides no explicit mechanism for structured inter-channel interaction. We introd…
cs.LG2025
KO: Kinetics-inspired Neural Optimizer with PDE Simulation Approaches
Mingquan Feng, Yixin Huang, Yifan Fu +2
The design of effective optimization algorithms for neural networks remains a fundamental challenge, and most existing methods rely on heuristic extensions of gradient-based update…
cs.LG2022★ 4 cited
Learning Neural Hamiltonian Dynamics: A Methodological Overview
Zhijie Chen, Mingquan Feng, Junchi Yan +1
The past few years have witnessed an increased interest in learning Hamiltonian dynamics in deep learning frameworks. As an inductive bias based on physical laws, Hamiltonian dynam…