540 citations · 908 across the 23 of their papers we have counts for
5 papers · 1 filter
Asymptotic-Preserving Neural Networks for Multiscale Time-Dependent Linear Transport Equations
Shi Jin, Zheng Ma, Keke Wu
In this paper we develop a neural network for the numerical simulation of time-dependent linear transport equations with diffusive scaling and uncertainties. The goal of the networ…
MOD-Net: A Machine Learning Approach via Model-Operator-Data Network for Solving PDEs
Lulu Zhang, Tao Luo, Yaoyu Zhang +3
In this paper, we propose a a machine learning approach via model-operator-data network (MOD-Net) for solving PDEs. A MOD-Net is driven by a model to solve PDEs based on operator r…
An Upper Limit of Decaying Rate with Respect to Frequency in Deep Neural Network
Tao Luo, Zheng Ma, Zhiwei Wang +2
Deep neural network (DNN) usually learns the target function from low to high frequency, which is called frequency principle or spectral bias. This frequency principle sheds light…
Network Pruning via Resource Reallocation
Yuenan Hou, Zheng Ma, Chunxiao Liu +2
Channel pruning is broadly recognized as an effective approach to obtain a small compact model through eliminating unimportant channels from a large cumbersome network. Contemporar…
Linear Frequency Principle Model to Understand the Absence of Overfitting in Neural Networks
Yaoyu Zhang, Tao Luo, Zheng Ma +1
Why heavily parameterized neural networks (NNs) do not overfit the data is an important long standing open question. We propose a phenomenological model of the NN training to expla…