14 citations · 29 across the 4 of their papers we have counts for
5 papers
Introduction to dynamical mean-field theory of randomly connected neural networks with bidirectionally correlated couplings
Wenxuan Zou, Haiping Huang
Dynamical mean-field theory is a powerful physics tool used to analyze the typical behavior of neural networks, where neurons can be recurrently connected, or multiple layers of ne…
Statistical mechanics of continual learning: variational principle and mean-field potential
Chan Li, Zhenye Huang, Wenxuan Zou +1
An obstacle to artificial general intelligence is set by continual learning of multiple tasks of different nature. Recently, various heuristic tricks, both from machine learning an…
CoCo DistillNet: a Cross-layer Correlation Distillation Network for Pathological Gastric Cancer Segmentation
Wenxuan Zou, Muyi Sun
In recent years, deep convolutional neural networks have made significant advances in pathology image segmentation. However, pathology image segmentation encounters with a dilemma…
Ensemble perspective for understanding temporal credit assignment
Wenxuan Zou, Chan Li, Haiping Huang
Recurrent neural networks are widely used for modeling spatio-temporal sequences in both nature language processing and neural population dynamics. However, understanding the tempo…
Data-driven effective model shows a liquid-like deep learning
Wenxuan Zou, Haiping Huang
The geometric structure of an optimization landscape is argued to be fundamentally important to support the success of deep neural network learning. A direct computation of the lan…