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05/15/2023
Introduction to dynamical mean-field theory of generic random neural networks
Dynamical mean-field theory is a powerful physics tool used to analyze t...
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12/06/2022
Statistical mechanics of continual learning: variational principle and mean-field potential
An obstacle to artificial general intelligence is set by the continual l...
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03/16/2022
Graph Flow: Cross-layer Graph Flow Distillation for Dual-Efficient Medical Image Segmentation
With the development of deep convolutional neural networks, medical imag...
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08/27/2021
CoCo DistillNet: a Cross-layer Correlation Distillation Network for Pathological Gastric Cancer Segmentation
In recent years, deep convolutional neural networks have made significan...
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02/07/2021
Ensemble perspective for understanding temporal credit assignment
Recurrent neural networks are widely used for modeling spatio-temporal s...
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07/16/2020