引用次数
引用: 1,824
H-指数: 17
I10-指数 : 23
出版物: 34
Stochastic Gradient Geodesic MCMC Methods
Jun Zhu , Yang Song , Chang Liu
neural information processing systems 29 3009 -3017
18
2016
Riemannian Stein Variational Gradient Descent for Bayesian Inference
Jun Zhu , Chang Liu
arXiv: Machine Learning
61
2017
Variational annealing of GANs: A Langevin perspective
Lawrence Carin , Liqun Chen , Chang Liu , Ruiyi Zhang
international conference on machine learning 6176 -6185
17
2019
Message Passing Stein Variational Gradient Descent.
Ning Chen , Jingwei Zhuo , Jun Zhu , Bo Zhang
international conference on machine learning 6013 -6022
60
2018
Straight-Through Estimator as Projected Wasserstein Gradient Flow.
Lawrence Carin , Chunyuan Li , Dinghan Shen , Chang Liu
arXiv: Learning
9
2019
Invertible Image Rescaling
Tie-Yan Liu , Zhouchen Lin , Jiang Bian , Di He
arXiv: Image and Video Processing
114
2020
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference
Jun Zhu , Michael Zhu , Chang Liu
international conference on machine learning 1 11576 -11587
11
2020
Modeling Lost Information in Lossy Image Compression.
Tie-Yan Liu , Chang Liu , Shuxin Zheng , Yaolong Wang
arXiv: Computer Vision and Pattern Recognition
13
2020
Learning to Match Distributions for Domain Adaptation
Renjun Xu , Tie-Yan Liu , Yiqiang Chen , Tao Qin
arXiv: Learning
7
2020
Learning Causal Semantic Representation for Out-of-Distribution Prediction
Chang Liu , Xinwei Sun , Jindong Wang , Haoyue Tang
arXiv: Machine Learning
36
2021
Generalizing to Unseen Domains: A Survey on Domain Generalization.
Jindong Wang , Cuiling Lan , Chang Liu , Yidong Ouyang
arXiv: Learning
278
2021
Rapid Inference of Nitrogen Oxide Emissions Based on a Top-Down Method with a Physically Informed Variational Autoencoder
Jia Xing , Siwei Li , Shuxin Zheng , Chang Liu
Environmental Science \& Technology 56 ( 14) 9903 -9914
2022
Benchmarking graphormer on large-scale molecular modeling datasets
Yu Shi , Shuxin Zheng , Guolin Ke , Yifei Shen
arXiv preprint arXiv:2203.04810
13
2022
Invertible rescaling network and its extensions
Mingqing Xiao , Shuxin Zheng , Chang Liu , Zhouchen Lin
International Journal of Computer Vision 131 ( 1) 134 -159
1
2023
Recovering latent causal factor for generalization to distributional shifts
Xinwei Sun , Botong Wu , Xiangyu Zheng , Chang Liu
Advances in Neural Information Processing Systems 34 16846 -16859
14
2021
Object-aware regularization for addressing causal confusion in imitation learning
Jongjin Park , Younggyo Seo , Chang Liu , Li Zhao
Advances in Neural Information Processing Systems 34 3029 -3042
7
2021
Direct molecular conformation generation
Jinhua Zhu , Yingce Xia , Chang Liu , Lijun Wu
arXiv preprint arXiv:2202.01356
41
2022
Predicting equilibrium distributions for molecular systems with deep learning
Shuxin Zheng , Jiyan He , Chang Liu , Yu Shi
Nature Machine Intelligence 1 -10
35
2024
Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning
He Zhang , Siyuan Liu , Jiacheng You , Chang Liu
Nature Computational Science 1 -14
2
2024
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Han Yang , Chenxi Hu , Yichi Zhou , Xixian Liu
arXiv preprint arXiv:2405.04967
2024