Search Results for author: Senwei Liang

Found 19 papers, 8 papers with code

Solving High-Dimensional Partial Integral Differential Equations: The Finite Expression Method

no code implementations1 Oct 2024 Gareth Hardwick, Senwei Liang, Haizhao Yang

In this paper, we introduce a new finite expression method (FEX) to solve high-dimensional partial integro-differential equations (PIDEs).

Computational Efficiency

Learning nonlinear integral operators via Recurrent Neural Networks and its application in solving Integro-Differential Equations

no code implementations13 Oct 2023 Hardeep Bassi, Yuanran Zhu, Senwei Liang, Jia Yin, Cian C. Reeves, Vojtech Vlcek, Chao Yang

In this paper, we propose using LSTM-RNNs (Long Short-Term Memory-Recurrent Neural Networks) to learn and represent nonlinear integral operators that appear in nonlinear integro-differential equations (IDEs).

Numerical Integration

Probing reaction channels via reinforcement learning

no code implementations27 May 2023 Senwei Liang, Aditya N. Singh, Yuanran Zhu, David T. Limmer, Chao Yang

We propose a reinforcement learning based method to identify important configurations that connect reactant and product states along chemical reaction paths.

reinforcement-learning Reinforcement Learning

A Generic Shared Attention Mechanism for Various Backbone Neural Networks

no code implementations27 Oct 2022 Zhongzhan Huang, Senwei Liang, Mingfu Liang, Liang Lin

The self-attention mechanism has emerged as a critical component for improving the performance of various backbone neural networks.

Data Augmentation Image Classification +3

On Fast Simulation of Dynamical System with Neural Vector Enhanced Numerical Solver

1 code implementation7 Aug 2022 Zhongzhan Huang, Senwei Liang, Hong Zhang, Haizhao Yang, Liang Lin

The large-scale simulation of dynamical systems is critical in numerous scientific and engineering disciplines.

Computational Efficiency

The Lottery Ticket Hypothesis for Self-attention in Convolutional Neural Network

no code implementations16 Jul 2022 Zhongzhan Huang, Senwei Liang, Mingfu Liang, wei he, Haizhao Yang, Liang Lin

Recently many plug-and-play self-attention modules (SAMs) are proposed to enhance the model generalization by exploiting the internal information of deep convolutional neural networks (CNNs).

Crowd Counting

Finite Expression Method for Solving High-Dimensional Partial Differential Equations

1 code implementation21 Jun 2022 Senwei Liang, Haizhao Yang

Designing efficient and accurate numerical solvers for high-dimensional partial differential equations (PDEs) remains a challenging and important topic in computational science and engineering, mainly due to the "curse of dimensionality" in designing numerical schemes that scale in dimension.

Deep Reinforcement Learning Vocal Bursts Intensity Prediction

Stiffness-aware neural network for learning Hamiltonian systems

no code implementations ICLR 2022 Senwei Liang, Zhongzhan Huang, Hong Zhang

We propose stiffness-aware neural network (SANN), a new method for learning Hamiltonian dynamical systems from data.

Stationary Density Estimation of Itô Diffusions Using Deep Learning

no code implementations9 Sep 2021 Yiqi Gu, John Harlim, Senwei Liang, Haizhao Yang

In this paper, we consider the density estimation problem associated with the stationary measure of ergodic It\^o diffusions from a discrete-time series that approximate the solutions of the stochastic differential equations.

Deep Learning Density Estimation +3

AlterSGD: Finding Flat Minima for Continual Learning by Alternative Training

no code implementations13 Jul 2021 Zhongzhan Huang, Mingfu Liang, Senwei Liang, wei he

Deep neural networks suffer from catastrophic forgetting when learning multiple knowledge sequentially, and a growing number of approaches have been proposed to mitigate this problem.

Continual Learning Semantic Segmentation

Blending Pruning Criteria for Convolutional Neural Networks

no code implementations11 Jul 2021 wei he, Zhongzhan Huang, Mingfu Liang, Senwei Liang, Haizhao Yang

One filter could be important according to a certain criterion, while it is unnecessary according to another one, which indicates that each criterion is only a partial view of the comprehensive "importance".

Clustering Network Pruning

Solving PDEs on Unknown Manifolds with Machine Learning

1 code implementation12 Jun 2021 Senwei Liang, Shixiao W. Jiang, John Harlim, Haizhao Yang

In a well-posed elliptic PDE setting, when the hypothesis space consists of neural networks with either infinite width or depth, we show that the global minimizer of the empirical loss function is a consistent solution in the limit of large training data.

BIG-bench Machine Learning Learning Theory

Reproducing Activation Function for Deep Learning

no code implementations13 Jan 2021 Senwei Liang, Liyao Lyu, Chunmei Wang, Haizhao Yang

We propose reproducing activation functions (RAFs) to improve deep learning accuracy for various applications ranging from computer vision to scientific computing.

Deep Learning Image Reconstruction +1

Quantifying Spatial Homogeneity of Urban Road Networks via Graph Neural Networks

1 code implementation1 Jan 2021 Jiawei Xue, Nan Jiang, Senwei Liang, Qiyuan Pang, Takahiro Yabe, Satish V. Ukkusuri, Jianzhu Ma

We apply the method to 11, 790 urban road networks across 30 cities worldwide to measure the spatial homogeneity of road networks within each city and across different cities.

Efficient Attention Network: Accelerate Attention by Searching Where to Plug

1 code implementation28 Nov 2020 Zhongzhan Huang, Senwei Liang, Mingfu Liang, wei he, Haizhao Yang

Recently, many plug-and-play self-attention modules are proposed to enhance the model generalization by exploiting the internal information of deep convolutional neural networks (CNNs).

Machine Learning for Prediction with Missing Dynamics

no code implementations13 Oct 2019 John Harlim, Shixiao W. Jiang, Senwei Liang, Haizhao Yang

This article presents a general framework for recovering missing dynamical systems using available data and machine learning techniques.

BIG-bench Machine Learning

Instance Enhancement Batch Normalization: an Adaptive Regulator of Batch Noise

2 code implementations12 Aug 2019 Senwei Liang, Zhongzhan Huang, Mingfu Liang, Haizhao Yang

Batch Normalization (BN)(Ioffe and Szegedy 2015) normalizes the features of an input image via statistics of a batch of images and hence BN will bring the noise to the gradient of the training loss.

Image Classification

DIANet: Dense-and-Implicit Attention Network

3 code implementations25 May 2019 Zhongzhan Huang, Senwei Liang, Mingfu Liang, Haizhao Yang

Attention networks have successfully boosted the performance in various vision problems.

Ranked #142 on Image Classification on CIFAR-100 (using extra training data)

Image Classification

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