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cs.LG2026
Neural solver for Wasserstein Geodesics and optimal transport dynamics
Hailiang Liu, Yan-Han Chen
In recent years, the machine learning community has increasingly embraced the optimal transport (OT) framework for modeling distributional relationships. In this work, we introduce…
cs.LG2025
Global Convergence in Neural ODEs: Impact of Activation Functions
Tianxiang Gao, Siyuan Sun, Hailiang Liu +1
Neural Ordinary Differential Equations (ODEs) have been successful in various applications due to their continuous nature and parameter-sharing efficiency. However, these unique ch…
cs.LG2023★ 3 cited
Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models
Tianxiang Gao, Xiaokai Huo, Hailiang Liu +1
Neural networks with wide layers have attracted significant attention due to their equivalence to Gaussian processes, enabling perfect fitting of training data while maintaining ge…