284 citations · 2k across the 95 of their papers we have counts for
4 papers · 2 filters
Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks
Chaoyu Liu, Zhonghua Qiao, Chao Li +1
Traditional image processing methods employing partial differential equations (PDEs) offer a multitude of meaningful regularizers, along with valuable theoretical foundations for a…
Alternating Local Enumeration (TnALE): Solving Tensor Network Structure Search with Fewer Evaluations
Chao Li, Junhua Zeng, Chunmei Li +2
Tensor network (TN) is a powerful framework in machine learning, but selecting a good TN model, known as TN structure search (TN-SS), is a challenging and computationally intensive…
Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks
Andong Wang, Chao Li, Mingyuan Bai +3
Achieving efficient and robust multi-channel data learning is a challenging task in data science. By exploiting low-rankness in the transformed domain, i.e., transformed low-rankne…
Centralized Cooperative Exploration Policy for Continuous Control Tasks
Chao Li, Chen Gong, Qiang He +2
The deep reinforcement learning (DRL) algorithm works brilliantly on solving various complex control tasks. This phenomenal success can be partly attributed to DRL encouraging inte…