Chang Liu

125 papers A* 46A 2Journal 71Unranked 6
YearRankTypeTitle / Venue / Authors
2026 A* conf
WaveFormer: Frequency-Time Decoupled Vision Modeling with Wave Equation.
AAAI
Zishan Shu, Juntong Wu, Wei Yan, Xudong Liu, Hongyu Zhang, Chang Liu, Youdong Mao, Jie Chen
2026 J jnl
WaveFormer: Frequency-Time Decoupled Vision Modeling with Wave Equation.
CoRR
Zishan Shu, Juntong Wu, Wei Yan, Xudong Liu, Hongyu Zhang, Chang Liu, Youdong Mao, Jie Chen
2025 J jnl
Adaptive Fuzzy Positive Learning for Annotation-Scarce Semantic Segmentation.
Int. J. Comput. Vis.
Pengchong Qiao, Yu Wang, Chang Liu, Lei Shang, Baigui Sun, Zhennan Wang, Xiawu Zheng, Rongrong Ji, Jie Chen
2025 J jnl
Diagnosing and Improving Diffusion Models by Estimating the Optimal Loss Value.
CoRR
Yixian Xu, Shengjie Luo, Liwei Wang, Di He, Chang Liu
2025 A* conf
DigitalLLaVA: Incorporating Digital Cognition Capability for Physical World Comprehension in Multimodal LLMs.
AAAI
Shiyu Li, Pengxu Wei, Pengchong Qiao, Chang Liu, Jie Chen
2025 J jnl
E2Former: A Linear-time Efficient and Equivariant Transformer for Scalable Molecular Modeling.
CoRR
Yunyang Li, Lin Huang, Zhihao Ding, Chu Wang, Xinran Wei, Han Yang, Zun Wang, Chang Liu, Yu Shi, Peiran Jin, Jia Zhang, Mark Gerstein, Tao Qin
2025 A* conf
Efficient ANN-SNN Conversion with Error Compensation Learning.
ICML
Chang Liu, Jiangrong Shen, Xuming Ran, Mingkun Xu, Qi Xu, Yi Xu, Gang Pan
2025 J jnl
Efficient ANN-SNN Conversion with Error Compensation Learning.
CoRR
Chang Liu, Jiangrong Shen, Xuming Ran, Mingkun Xu, Qi Xu, Yi Xu, Gang Pan
2025 A* conf
Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity.
ICML
Erpai Luo, Xinran Wei, Lin Huang, Yunyang Li, Han Yang, Zaishuo Xia, Zun Wang, Chang Liu, Bin Shao, Jia Zhang
2025 A* conf
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems.
ICLR
Yunyang Li, Zaishuo Xia, Lin Huang, Xinran Wei, Samuel Harshe, Han Yang, Erpai Luo, Zun Wang, Jia Zhang, Chang Liu, Bin Shao, Mark Gerstein
2025 J jnl
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems.
CoRR
Yunyang Li, Zaishuo Xia, Lin Huang, Xinran Wei, Han Yang, Sam Harshe, Zun Wang, Chang Liu, Jia Zhang, Bin Shao, Mark B. Gerstein
2025 A* conf
Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning.
AAAI
Yun Qu, Yuhang Jiang, Boyuan Wang, Yixiu Mao, Cheems Wang, Chang Liu, Xiangyang Ji
2025 J jnl
Loomis Painter: Reconstructing the Painting Process.
CoRR
Markus Pobitzer, Chang Liu, Chenyi Zhuang, Teng Long, Bin Ren, Nicu Sebe
2025 J jnl
MagicComp: Training-free Dual-Phase Refinement for Compositional Video Generation.
CoRR
Hongyu Zhang, Yufan Deng, Shenghai Yuan, Peng Jin, Zesen Cheng, Yian Zhao, Chang Liu, Jie Chen
2025 J jnl
NatureLM: Deciphering the Language of Nature for Scientific Discovery.
CoRR
Yingce Xia, Peiran Jin, Shufang Xie, Liang He, Chuan Cao, Renqian Luo, Guoqing Liu, Yue Wang, Zequn Liu, Yuan-Jyue Chen, Zekun Guo, Yeqi Bai, Pan Deng, Yaosen Min, Ziheng Lu, Hongxia Hao, Han Yang, Jielan Li, Chang Liu, Jia Zhang, Jianwei Zhu, Kehan Wu, Wei Zhang, Kaiyuan Gao, Qizhi Pei, Qian Wang, Xixian Liu, Yanting Li, Houtian Zhu, Yeqing Lu, Mingqian Ma, Zun Wang, Tian Xie, Krzysztof Maziarz, Marwin H. S. Segler, Zhao Yang, Zilong Chen, Yu Shi, Shuxin Zheng, Lijun Wu, Chen Hu, Peggy Dai, Tie-Yan Liu, Haiguang Liu, Tao Qin
2025 J jnl
Potential Score Matching: Debiasing Molecular Structure Sampling with Potential Energy Guidance.
CoRR
Liya Guo, Zun Wang, Chang Liu, Junzhe Li, Pipi Hu, Yi Zhu
2025 J jnl
Potential Score Matching: Debiasing Molecular Structure Sampling with Potential Energy Guidance.
Trans. Mach. Learn. Res.
Liya Guo, Zun Wang, Chang Liu, Junzhe Li, Pipi Hu, Yi Zhu, Tao Qin
2025 A conf
Spherical Scissor-Like Reconfigurable Palm Design in Robotic Hands: Insights from Human Hand Functionality.
IROS
Jiaxing Wang, Fang Zhang, Kai Chen, Chang Liu, Guoniu Zhu, Qiujie Lu, Zhongxue Gan
2025 J jnl
UI2V-Bench: An Understanding-based Image-to-video Generation Benchmark.
CoRR
Ailing Zhang, Lina Lei, Dehong Kong, Zhixin Wang, Jiaqi Xu, Fenglong Song, Chun-Le Guo, Chang Liu, Fan Li, Jie Chen
2025 J jnl
UniGenX: Unified Generation of Sequence and Structure with Autoregressive Diffusion.
CoRR
Gongbo Zhang, Yanting Li, Renqian Luo, Pipi Hu, Zeru Zhao, Lingbo Li, Guoqing Liu, Zun Wang, Ran Bi, Kaiyuan Gao, Liya Guo, Yu Xie, Chang Liu, Jia Zhang, Tian Xie, Robert Pinsler, Claudio Zeni, Ziheng Lu, Yingce Xia, Marwin H. S. Segler, Maik Riechert, Li Yuan, Lei Chen, Haiguang Liu, Tao Qin
2024 J jnl
Author Correction: Predicting equilibrium distributions for molecular systems with deep learning.
Nat. Mac. Intell.
Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu
2024 J jnl
Choices are More Important than Efforts: LLM Enables Efficient Multi-Agent Exploration.
CoRR
Yun Qu, Boyuan Wang, Yuhang Jiang, Jianzhun Shao, Yixiu Mao, Cheems Wang, Chang Liu, Xiangyang Ji
2024 A* conf
FaceChain-SuDe: Building Derived Class to Inherit Category Attributes for One-Shot Subject-Driven Generation.
CVPR
Pengchong Qiao, Lei Shang, Chang Liu, Baigui Sun, Xiangyang Ji, Jie Chen
2024 J jnl
FaceChain-SuDe: Building Derived Class to Inherit Category Attributes for One-shot Subject-Driven Generation.
CoRR
Pengchong Qiao, Lei Shang, Chang Liu, Baigui Sun, Xiangyang Ji, Jie Chen
2024 — conf
From Synthetic to Real: A Calibration-free Pipeline for Few-shot Raw Image Denoising.
CVPR Workshops
Ruoqi Li, Chang Liu, Ziyi Wang, Yao Du, Jingjing Yang, Long Bao, Heng Sun
2024 A* conf
GraCo: Granularity-Controllable Interactive Segmentation.
CVPR
Yian Zhao, Kehan Li, Zesen Cheng, Pengchong Qiao, Xiawu Zheng, Rongrong Ji, Chang Liu, Li Yuan, Jie Chen
2024 J jnl
GraCo: Granularity-Controllable Interactive Segmentation.
CoRR
Yian Zhao, Kehan Li, Zesen Cheng, Pengchong Qiao, Xiawu Zheng, Rongrong Ji, Chang Liu, Li Yuan, Jie Chen
2024 A* conf
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models.
NeurIPS
Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran Wei, Lin Huang, Lijun Wu, Bin Shao
2024 J jnl
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models.
CoRR
Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran Wei, Lin Huang, Lijun Wu, Bin Shao
2024 J jnl
Instance Brownian Bridge as Texts for Open-vocabulary Video Instance Segmentation.
CoRR
Zesen Cheng, Kehan Li, Hao Li, Peng Jin, Chang Liu, Xiawu Zheng, Rongrong Ji, Jie Chen
2024 A* conf
Kepler codebook.
ICML
Junrong Lian, Ziyue Dong, Pengxu Wei, Wei Ke, Chang Liu, Qixiang Ye, Xiangyang Ji, Liang Lin
2024 A* conf
LLM-Empowered State Representation for Reinforcement Learning.
ICML
Boyuan Wang, Yun Qu, Yuhang Jiang, Jianzhun Shao, Chang Liu, Wenming Yang, Xiangyang Ji
2024 J jnl
LLM-Empowered State Representation for Reinforcement Learning.
CoRR
Boyuan Wang, Yun Qu, Yuhang Jiang, Jianzhun Shao, Chang Liu, Wenming Yang, Xiangyang Ji
2024 J jnl
Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning.
CoRR
Yun Qu, Yuhang Jiang, Boyuan Wang, Yixiu Mao, Cheems Wang, Chang Liu, Xiangyang Ji
2024 J jnl
Local Action-Guided Motion Diffusion Model for Text-to-Motion Generation.
CoRR
Peng Jin, Hao Li, Zesen Cheng, Kehan Li, Runyi Yu, Chang Liu, Xiangyang Ji, Li Yuan, Jie Chen
2024 — conf
MIPI 2024 Challenge on Few-shot RAW Image Denoising: Methods and Results.
CVPR Workshops
Xin Jin, Chunle Guo, Xiaoming Li, Zongsheng Yue, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Yuekun Dai, Peiqing Yang, Chen Change Loy, Ruoqi Li, Chang Liu, Ziyi Wang, Yao Du, Jingjing Yang, Long Bao, Heng Sun, Xiangyu Kong, Xiaoxia Xing, Jinlong Wu, Yuanyang Xue, Hyunhee Park, Sejun Song, Changho Kim, Jingfan Tan, Wenhan Luo, Zikun Liu, Mingde Qiao, Junjun Jiang, Kui Jiang, Yao Xiao, Chuyang Sun, Jinhui Hu, Weijian Ruan, Yubo Dong, Kai Chen, Hyejeong Jo, Jiahao Qin, Bingjie Han, Pinle Qin, Rui Chai, Pengyuan Wang
2024 J jnl
MIPI 2024 Challenge on Few-shot RAW Image Denoising: Methods and Results.
CoRR
Xin Jin, Chunle Guo, Xiaoming Li, Zongsheng Yue, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Yuekun Dai, Peiqing Yang, Chen Change Loy, Ruoqi Li, Chang Liu, Ziyi Wang, Yao Du, Jingjing Yang, Long Bao, Heng Sun, Xiangyu Kong, Xiaoxia Xing, Jinlong Wu, Yuanyang Xue, Hyunhee Park, Sejun Song, Changho Kim, Jingfan Tan, Wenhan Luo, Zikun Liu, Mingde Qiao, Junjun Jiang, Kui Jiang, Yao Xiao, Chuyang Sun, Jinhui Hu, Weijian Ruan, Yubo Dong, Kai Chen, Hyejeong Jo, Jiahao Qin, Bingjie Han, Pinle Qin, Rui Chai, Pengyuan Wang
2024 J jnl
Make Your Actor Talk: Generalizable and High-Fidelity Lip Sync with Motion and Appearance Disentanglement.
CoRR
Runyi Yu, Tianyu He, Ailing Zhang, Yuchi Wang, Junliang Guo, Xu Tan, Chang Liu, Jie Chen, Jiang Bian
2024 J jnl
Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning.
Nat. Comput. Sci.
He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao
2024 — conf
ParCo: Part-Coordinating Text-to-Motion Synthesis.
ECCV (56)
Qiran Zou, Shangyuan Yuan, Shian Du, Yu Wang, Chang Liu, Yi Xu, Jie Chen, Xiangyang Ji
2024 J jnl
ParCo: Part-Coordinating Text-to-Motion Synthesis.
CoRR
Qiran Zou, Shangyuan Yuan, Shian Du, Yu Wang, Chang Liu, Yi Xu, Jie Chen, Xiangyang Ji
2024 A* conf
Parallel Vertex Diffusion for Unified Visual Grounding.
AAAI
Zesen Cheng, Kehan Li, Peng Jin, Siheng Li, Xiangyang Ji, Li Yuan, Chang Liu, Jie Chen
2024 A* conf
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning.
NeurIPS
Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu
2024 J jnl
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning.
CoRR
Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu
2024 J jnl
Predicting equilibrium distributions for molecular systems with deep learning.
Nat. Mac. Intell.
Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu
2024 A* conf
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction.
ICML
He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu
2024 J jnl
Self-Consistency Training for Hamiltonian Prediction.
CoRR
He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu
2024 A* conf
UVMap-ID: A Controllable and Personalized UV Map Generative Model.
ACM Multimedia
Weijie Wang, Jichao Zhang, Chang Liu, Xia Li, Xingqian Xu, Humphrey Shi, Nicu Sebe, Bruno Lepri
2024 J jnl
UVMap-ID: A Controllable and Personalized UV Map Generative Model.
CoRR
Weijie Wang, Jichao Zhang, Chang Liu, Xia Li, Xingqian Xu, Humphrey Shi, Nicu Sebe, Bruno Lepri
2023 A* conf
ACSeg: Adaptive Conceptualization for Unsupervised Semantic Segmentation.
CVPR
Kehan Li, Zhennan Wang, Zesen Cheng, Runyi Yu, Yian Zhao, Guoli Song, Chang Liu, Li Yuan, Jie Chen
2023 A* conf
Complementary Attention for Multi-Agent Reinforcement Learning.
ICML
Jianzhun Shao, Hongchang Zhang, Yun Qu, Chang Liu, Shuncheng He, Yuhang Jiang, Xiangyang Ji
2023 A* conf
DiffusionRet: Generative Text-Video Retrieval with Diffusion Model.
ICCV
Peng Jin, Hao Li, Zesen Cheng, Kehan Li, Xiangyang Ji, Chang Liu, Li Yuan, Jie Chen
2023 J jnl
DiffusionRet: Generative Text-Video Retrieval with Diffusion Model.
CoRR
Peng Jin, Hao Li, Zesen Cheng, Kehan Li, Xiangyang Ji, Chang Liu, Li Yuan, Jie Chen
2023 A* conf
Discover and Align Taxonomic Context Priors for Open-world Semi-Supervised Learning.
NeurIPS
Yu Wang, Zhun Zhong, Pengchong Qiao, Xuxin Cheng, Xiawu Zheng, Chang Liu, Nicu Sebe, Rongrong Ji, Jie Chen
2023 J jnl
Disjoint Masking with Joint Distillation for Efficient Masked Image Modeling.
CoRR
Xin Ma, Chang Liu, Chunyu Xie, Long Ye, Yafeng Deng, Xiangyang Ji
2023 J jnl
FreestyleRet: Retrieving Images from Style-Diversified Queries.
CoRR
Hao Li, Curise Jia, Peng Jin, Zesen Cheng, Kehan Li, Jialu Sui, Chang Liu, Li Yuan
2023 A* conf
Fuzzy Positive Learning for Semi-Supervised Semantic Segmentation.
CVPR
Pengchong Qiao, Zhidan Wei, Yu Wang, Zhennan Wang, Guoli Song, Fan Xu, Xiangyang Ji, Chang Liu, Jie Chen
2023 J jnl
Generalizing to Unseen Domains: A Survey on Domain Generalization.
IEEE Trans. Knowl. Data Eng.
Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin, Wang Lu, Yiqiang Chen, Wenjun Zeng, Philip S. Yu
2023 A* conf
ILSGAN: Independent Layer Synthesis for Unsupervised Foreground-Background Segmentation.
AAAI
Qiran Zou, Yu Yang, Wing Yin Cheung, Chang Liu, Xiangyang Ji
2023 J jnl
Invertible Rescaling Network and Its Extensions.
Int. J. Comput. Vis.
Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu
2023 A* conf
LaPE: Layer-adaptive Position Embedding for Vision Transformers with Independent Layer Normalization.
ICCV
Runyi Yu, Zhennan Wang, Yinhuai Wang, Kehan Li, Chang Liu, Haoyi Duan, Xiangyang Ji, Jie Chen
2023 J jnl
M-OFDFT: Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning.
CoRR
He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao
2023 A* conf
Multi-granularity Interaction Simulation for Unsupervised Interactive Segmentation.
ICCV
Kehan Li, Yian Zhao, Zhennan Wang, Zesen Cheng, Peng Jin, Xiangyang Ji, Li Yuan, Chang Liu, Jie Chen
2023 J jnl
Multi-granularity Interaction Simulation for Unsupervised Interactive Segmentation.
CoRR
Kehan Li, Yian Zhao, Zhennan Wang, Zesen Cheng, Peng Jin, Xiangyang Ji, Li Yuan, Chang Liu, Jie Chen
2023 A* conf
Out-of-Candidate Rectification for Weakly Supervised Semantic Segmentation.
CVPR
Zesen Cheng, Pengchong Qiao, Kehan Li, Siheng Li, Pengxu Wei, Xiangyang Ji, Li Yuan, Chang Liu, Jie Chen
2023 A* conf
Out-of-Distributed Semantic Pruning for Robust Semi-Supervised Learning.
CVPR
Yu Wang, Pengchong Qiao, Chang Liu, Guoli Song, Xiawu Zheng, Jie Chen
2023 J jnl
Out-of-Distributed Semantic Pruning for Robust Semi-Supervised Learning.
CoRR
Yu Wang, Pengchong Qiao, Chang Liu, Guoli Song, Xiawu Zheng, Jie Chen
2023 J jnl
Parallel Vertex Diffusion for Unified Visual Grounding.
CoRR
Zesen Cheng, Kehan Li, Peng Jin, Xiangyang Ji, Li Yuan, Chang Liu, Jie Chen
2023 A conf
Spatio-Temporal Graph Diffusion for Text-Driven Human Motion Generation.
BMVC
Chang Liu, Mengyi Zhao, Bin Ren, Mengyuan Liu, Nicu Sebe
2023 A* conf
TG-VQA: Ternary Game of Video Question Answering.
IJCAI
Hao Li, Peng Jin, Zesen Cheng, Songyang Zhang, Kai Chen, Zhennan Wang, Chang Liu, Jie Chen
2023 J jnl
TG-VQA: Ternary Game of Video Question Answering.
CoRR
Hao Li, Peng Jin, Zesen Cheng, Songyang Zhang, Kai Chen, Zhennan Wang, Chang Liu, Jie Chen
2023 A* conf
Text-Video Retrieval with Disentangled Conceptualization and Set-to-Set Alignment.
IJCAI
Peng Jin, Hao Li, Zesen Cheng, Jinfa Huang, Zhennan Wang, Li Yuan, Chang Liu, Jie Chen
2023 J jnl
Text-Video Retrieval with Disentangled Conceptualization and Set-to-Set Alignment.
CoRR
Peng Jin, Hao Li, Zesen Cheng, Jinfa Huang, Zhennan Wang, Li Yuan, Chang Liu, Jie Chen
2023 A* conf
TopoSeg: Topology-Aware Nuclear Instance Segmentation.
ICCV
Hongliang He, Jun Wang, Pengxu Wei, Fan Xu, Xiangyang Ji, Chang Liu, Jie Chen
2023 J jnl
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning.
CoRR
Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu
2023 A* conf
Towards Real-World Burst Image Super-Resolution: Benchmark and Method.
ICCV
Pengxu Wei, Yujing Sun, Xingbei Guo, Chang Liu, Guanbin Li, Jie Chen, Xiangyang Ji, Liang Lin
2023 J jnl
Towards Real-World Burst Image Super-Resolution: Benchmark and Method.
CoRR
Pengxu Wei, Yujing Sun, Xingbei Guo, Chang Liu, Jie Chen, Xiangyang Ji, Liang Lin
2023 A* conf
Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning.
CVPR
Peng Jin, Jinfa Huang, Pengfei Xiong, Shangxuan Tian, Chang Liu, Xiangyang Ji, Li Yuan, Jie Chen
2023 J jnl
Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning.
CoRR
Peng Jin, Jinfa Huang, Pengfei Xiong, Shangxuan Tian, Chang Liu, Xiangyang Ji, Li Yuan, Jie Chen
2023 A* conf
WiCo: Win-win Cooperation of Bottom-up and Top-down Referring Image Segmentation.
IJCAI
Zesen Cheng, Peng Jin, Hao Li, Kehan Li, Siheng Li, Xiangyang Ji, Chang Liu, Jie Chen
2023 J jnl
WiCo: Win-win Cooperation of Bottom-up and Top-down Referring Image Segmentation.
CoRR
Zesen Cheng, Peng Jin, Hao Li, Kehan Li, Siheng Li, Xiangyang Ji, Chang Liu, Jie Chen
2022 J jnl
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets.
CoRR
Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu
2022 J jnl
DQnet: Cross-Model Detail Querying for Camouflaged Object Detection.
CoRR
Wei Sun, Chengao Liu, Linyan Zhang, Yu Li, Pengxu Wei, Chang Liu, Jialing Zou, Jianbin Jiao, Qixiang Ye
2022 J jnl
Direct Molecular Conformation Generation.
CoRR
Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Tong Wang, Yusong Wang, Wengang Zhou, Tao Qin, Houqiang Li, Tie-Yan Liu
2022 J jnl
Direct Molecular Conformation Generation.
Trans. Mach. Learn. Res.
Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Yusong Wang, Tong Wang, Tao Qin, Wengang Zhou, Houqiang Li, Haiguang Liu, Tie-Yan Liu
2022 A* conf
Distilling Representations from GAN Generator via Squeeze and Span.
NeurIPS
Yu Yang, Xiaotian Cheng, Chang Liu, Hakan Bilen, Xiangyang Ji
2022 J jnl
Distilling Representations from GAN Generator via Squeeze and Span.
CoRR
Yu Yang, Xiaotian Cheng, Chang Liu, Hakan Bilen, Xiangyang Ji
2022 J jnl
ILSGAN: Independent Layer Synthesis for Unsupervised Foreground-Background Segmentation.
CoRR
Qiran Zou, Yu Yang, Wing Yin Cheung, Chang Liu, Xiangyang Ji
2022 J jnl
Invertible Rescaling Network and Its Extensions.
CoRR
Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu
2022 J jnl
Local Manifold Augmentation for Multiview Semantic Consistency.
CoRR
Yu Yang, Wing Yin Cheung, Chang Liu, Xiangyang Ji
2022 J jnl
Out-of-Candidate Rectification for Weakly Supervised Semantic Segmentation.
CoRR
Zesen Cheng, Pengchong Qiao, Kehan Li, Siheng Li, Pengxu Wei, Xiangyang Ji, Li Yuan, Chang Liu, Jie Chen
2022 J jnl
PCR: Pessimistic Consistency Regularization for Semi-Supervised Segmentation.
CoRR
Pengchong Qiao, Zhidan Wei, Yu Wang, Chang Liu, Zhennan Wang, Guoli Song, Jie Chen
2022 A* conf
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior.
ICLR
Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu
2022 J jnl
Proposal Distribution Calibration for Few-Shot Object Detection.
CoRR
Bohao Li, Chang Liu, Mengnan Shi, Xiaozhong Chen, Xiangyang Ji, Qixiang Ye
2022 A* conf
Sampling with Mirrored Stein Operators.
ICLR
Jiaxin Shi, Chang Liu, Lester Mackey
2021 A* conf
Generalizing to Unseen Domains: A Survey on Domain Generalization.
IJCAI
Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin
2021 J jnl
Generalizing to Unseen Domains: A Survey on Domain Generalization.
CoRR
Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin
2021 A* conf
Learning Causal Semantic Representation for Out-of-Distribution Prediction.
NeurIPS
Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu
2021 J jnl
Learning Invariant Representations across Domains and Tasks.
CoRR
Jindong Wang, Wenjie Feng, Chang Liu, Chaohui Yu, Mingxuan Du, Renjun Xu, Tao Qin, Tie-Yan Liu
2021 A* conf
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning.
NeurIPS
Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu
2021 J jnl
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning.
CoRR
Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu
2021 A* conf
On the Generative Utility of Cyclic Conditionals.
NeurIPS
Chang Liu, Haoyue Tang, Tao Qin, Jintao Wang, Tie-Yan Liu
2021 J jnl
On the Generative Utility of Cyclic Conditionals.
CoRR
Chang Liu, Haoyue Tang, Tao Qin, Jintao Wang, Tie-Yan Liu
2021 J jnl
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior.
CoRR
Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu
2021 A* conf
Recovering Latent Causal Factor for Generalization to Distributional Shifts.
NeurIPS
Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu
2021 J jnl
Sampling with Mirrored Stein Operators.
CoRR
Jiaxin Shi, Chang Liu, Lester Mackey
2021 A* conf
Towards Generating Real-World Time Series Data.
ICDM
Hengzhi Pei, Kan Ren, Yuqing Yang, Chang Liu, Tao Qin, Dongsheng Li
2021 J jnl
Towards Generating Real-World Time Series Data.
CoRR
Hengzhi Pei, Kan Ren, Yuqing Yang, Chang Liu, Tao Qin, Dongsheng Li
2020 — conf
Invertible Image Rescaling.
ECCV (1)
Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu
2020 J jnl
Invertible Image Rescaling.
CoRR
Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu
2020 J jnl
Latent Causal Invariant Model.
CoRR
Xinwei Sun, Botong Wu, Chang Liu, Xiangyu Zheng, Wei Chen, Tao Qin, Tie-Yan Liu
2020 J jnl
Learning Causal Semantic Representation for Out-of-Distribution Prediction.
CoRR
Chang Liu, Xinwei Sun, Jindong Wang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu
2020 J jnl
Learning to Match Distributions for Domain Adaptation.
CoRR
Chaohui Yu, Jindong Wang, Chang Liu, Tao Qin, Renjun Xu, Wenjie Feng, Yiqiang Chen, Tie-Yan Liu
2020 J jnl
Modeling Lost Information in Lossy Image Compression.
CoRR
Yaolong Wang, Mingqing Xiao, Chang Liu, Shuxin Zheng, Tie-Yan Liu
2020 A* conf
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference.
ICML
Michael Zhu, Chang Liu, Jun Zhu
2019 J jnl
Straight-Through Estimator as Projected Wasserstein Gradient Flow.
CoRR
Pengyu Cheng, Chang Liu, Chunyuan Li, Dinghan Shen, Ricardo Henao, Lawrence Carin
2019 A* conf
Understanding MCMC Dynamics as Flows on the Wasserstein Space.
ICML
Chang Liu, Jingwei Zhuo, Jun Zhu
2019 J jnl
Understanding MCMC Dynamics as Flows on the Wasserstein Space.
CoRR
Chang Liu, Jingwei Zhuo, Jun Zhu
2019 A* conf
Understanding and Accelerating Particle-Based Variational Inference.
ICML
Chang Liu, Jingwei Zhuo, Pengyu Cheng, Ruiyi Zhang, Jun Zhu
2019 A* conf
Variational Annealing of GANs: A Langevin Perspective.
ICML
Chenyang Tao, Shuyang Dai, Liqun Chen, Ke Bai, Junya Chen, Chang Liu, Ruiyi Zhang, Georgiy V. Bobashev, Lawrence Carin
2018 J jnl
Accelerated First-order Methods on the Wasserstein Space for Bayesian Inference.
CoRR
Chang Liu, Jingwei Zhuo, Pengyu Cheng, Ruiyi Zhang, Jun Zhu, Lawrence Carin
2018 A* conf
Message Passing Stein Variational Gradient Descent.
ICML
Jingwei Zhuo, Chang Liu, Jiaxin Shi, Jun Zhu, Ning Chen, Bo Zhang
2018 A* conf
Riemannian Stein Variational Gradient Descent for Bayesian Inference.
AAAI
Chang Liu, Jun Zhu
2016 — conf
Stochastic Gradient Geodesic MCMC Methods.
NIPS
Chang Liu, Jun Zhu, Yang Song
2015 — conf
Research and simulation for an ultra-high-speed mobile broadband multimedia transmission system.
BMSB
Chang Liu, Jintao Wang, Hui Yang, Chang-Yong Pan