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Chang Liu
Chang Liu
Microsoft Research AI for Science
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Generalizing to unseen domains: A survey on domain generalization
J Wang, C Lan, C Liu, Y Ouyang, T Qin, W Lu, Y Chen, W Zeng, SY Philip
IEEE transactions on knowledge and data engineering 35 (8), 8052-8072, 2022
10592022
Invertible image rescaling
M Xiao, S Zheng, C Liu, Y Wang, D He, G Ke, J Bian, Z Lin, TY Liu
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
2592020
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior
S Lee, H Kim, C Shin, X Tan, C Liu, Q Meng, T Qin, W Chen, S Yoon, ...
International Conference on Learning Representations, 2022
114*2022
Understanding and Accelerating Particle-Based Variational Inference
C Liu, J Zhuo, P Cheng, R Zhang, J Zhu, L Carin
International Conference on Machine Learning, 4082--4092, 2019
114*2019
Learning Causal Semantic Representation for Out-of-Distribution Prediction
C Liu, X Sun, J Wang, H Tang, T Li, T Qin, W Chen, TY Liu
Advances in Neural Information Processing Systems 34, 2021
1132021
Message Passing Stein Variational Gradient Descent
J Zhuo, C Liu, J Shi, J Zhu, N Chen, B Zhang
International Conference on Machine Learning, 2018
982018
Predicting equilibrium distributions for molecular systems with deep learning
S Zheng, J He, C Liu, Y Shi, Z Lu, W Feng, F Ju, J Wang, J Zhu, Y Min, ...
Nature Machine Intelligence, 1-10, 2024
73*2024
Recovering Latent Causal Factor for Generalization to Distributional Shifts
X Sun, B Wu, X Zheng, C Liu, W Chen, T Qin, TY Liu
Advances in Neural Information Processing Systems 34, 2021
73*2021
Riemannian Stein Variational Gradient Descent for Bayesian Inference
C Liu, J Zhu
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
702018
Benchmarking graphormer on large-scale molecular modeling datasets
Y Shi, S Zheng, G Ke, Y Shen, J You, J He, S Luo, C Liu, D He, TY Liu
arXiv preprint arXiv:2203.04810, 2022
662022
Direct Molecular Conformation Generation
J Zhu, Y Xia, C Liu, L Wu, S Xie, T Wang, Y Wang, W Zhou, T Qin, H Li, ...
Transactions on Machine Learning Research, 2022
512022
Towards Generating Real-World Time Series Data
H Pei, K Ren, Y Yang, C Liu, T Qin, D Li
2021 IEEE International Conference on Data Mining (ICDM), 469-478, 2021
462021
Stochastic Gradient Geodesic MCMC Methods
C Liu, J Zhu, Y Song
Advances in Neural Information Processing Systems, 3009-3017, 2016
362016
The impact of large language models on scientific discovery: a preliminary study using gpt-4
MR AI4Science, MA Quantum
arXiv preprint arXiv:2311.07361, 2023
352023
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning
J Park, Y Seo, C Liu, L Zhao, T Qin, J Shin, TY Liu
Advances in Neural Information Processing Systems 34, 3029-3042, 2021
272021
Modeling Lost Information in Lossy Image Compression
Y Wang, M Xiao, C Liu, S Zheng, TY Liu
arXiv preprint arXiv:2006.11999, 2020
272020
Sampling with Mirrored Stein Operators
J Shi, C Liu, L Mackey
International Conference on Learning Representations, 2022
262022
Understanding MCMC Dynamics as Flows on the Wasserstein Space
C Liu, J Zhuo, J Zhu
International Conference on Machine Learning, 4093--4103, 2019
252019
Invertible Rescaling Network and Its Extensions
M Xiao, S Zheng, C Liu, Z Lin, TY Liu
International Journal of Computer Vision 131 (1), 134-159, 2023
232023
Variational Annealing of GANs: A Langevin Perspective
C Tao, S Dai, L Chen, K Bai, J Chen, C Liu, R Zhang, G Bobashev, ...
International Conference on Machine Learning, 6176-6185, 2019
232019
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Articles 1–20