Zhang, Cheng

108 publications

TMLR 2025 Amortized Inference of Causal Models via Conditional Fixed-Point Iterations Divyat Mahajan, Jannes Gladrow, Agrin Hilmkil, Cheng Zhang, Meyer Scetbon

ICML 2025 Continuous Semi-Implicit Models Longlin Yu, Jiajun Zha, Tong Yang, Tianyu Xie, Xiangyu Zhang, S.-H. Chan, Cheng Zhang

CVPR 2025 Digital Twin Catalog: A Large-Scale Photorealistic 3D Object Digital Twin Dataset Zhao Dong, Ka Chen, Zhaoyang Lv, Hong-Xing Yu, Yunzhi Zhang, Cheng Zhang, Yufeng Zhu, Stephen Tian, Zhengqin Li, Geordie Moffatt, Sean Christofferson, James Fort, Xiaqing Pan, Mingfei Yan, Jiajun Wu, Carl Yuheng Ren, Richard Newcombe

CVPR 2025 HVI: A New Color Space for Low-Light Image Enhancement Qingsen Yan, Yixu Feng, Cheng Zhang, Guansong Pang, Kangbiao Shi, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang

ICML 2025 Hardware and Software Platform Inference Cheng Zhang, Hanna Foerster, Robert D. Mullins, Yiren Zhao, Ilia Shumailov

CVPR 2025 PanSplat: 4k Panorama Synthesis with Feed-Forward Gaussian Splatting Cheng Zhang, Haofei Xu, Qianyi Wu, Camilo Cruz Gambardella, Dinh Phung, Jianfei Cai

CVPR 2025 Panorama Generation from NFoV Image Done Right Dian Zheng, Cheng Zhang, Xiao-Ming Wu, Cao Li, Chengfei Lv, Jian-Fang Hu, Wei-Shi Zheng

ICLR 2025 PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Tianyu Xie, Harry Richman, Jiansi Gao, Frederick A Matsen, Cheng Zhang

NeurIPS 2025 Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning Ziheng Cheng, Tianyu Xie, Shiyue Zhang, Cheng Zhang

ICLR 2025 QERA: An Analytical Framework for Quantization Error Reconstruction Cheng Zhang, Jeffrey T. H. Wong, Can Xiao, George Anthony Constantinides, Yiren Zhao

IJCAI 2025 Rethinking Removal Attack and Fingerprinting Defense for Model Intellectual Property Protection: A Frequency Perspective Cheng Zhang, Yang Xu, Tingqiao Huang, Zixing Zhang

ICCV 2025 TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation Amin Karimi Monsefi, Mridul Khurana, Rajiv Ramnath, Anuj Karpatne, Wei-Lun Chao, Cheng Zhang

ICML 2024 A Fixed-Point Approach for Causal Generative Modeling Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang, Chao Ma

JMLR 2024 A Variational Approach to Bayesian Phylogenetic Inference Cheng Zhang, Frederick A. Matsen Iv

ECCV 2024 An Empirical Study and Analysis of Text-to-Image Generation Using Large Language Model-Powered Textual Representation Zhiyu Tan, Mengping Yang, Luozheng Qin, Hao Yang, Ye Qian, Qiang Zhou, Cheng Zhang, Hao Li

TMLR 2024 Deep End-to-End Causal Inference Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang

AAAI 2024 EasyTS: The Express Lane to Long Time Series Forecasting Tiancheng Zhang, Shaoyuan Huang, Cheng Zhang, Xiaofei Wang, Wenyu Wang

NeurIPS 2024 Functional Gradient Flows for Constrained Sampling Shiyue Zhang, Longlin Yu, Ziheng Cheng, Cheng Zhang

ECCV 2024 Generalizable Human Gaussians for Sparse View Synthesis YoungJoong Kwon, Baole Fang, Yixing Lu, Haoye Dong, Cheng Zhang, Francisco Vicente Carrasco, Albert Mosella-Montoro, Jianjin Xu, Shingo J Takagi, Daeil Kim, Aayush Prakash, Fernando de la Torre

ICML 2024 Kernel Semi-Implicit Variational Inference Ziheng Cheng, Longlin Yu, Tianyu Xie, Shiyue Zhang, Cheng Zhang

ICML 2024 LQER: Low-Rank Quantization Error Reconstruction for LLMs Cheng Zhang, Jianyi Cheng, George Anthony Constantinides, Yiren Zhao

ECCV 2024 Make Your ViT-Based Multi-View 3D Detectors Faster via Token Compression Dingyuan Zhang, Dingkang Liang, Zichang Tan, Xiaoqing Ye, Cheng Zhang, Jingdong Wang, Xiang Bai

ICMLW 2024 Optimised Grouped-Query Attention Mechanism for Transformers Yuang Chen, Cheng Zhang, Xitong Gao, Robert D. Mullins, George Anthony Constantinides, Yiren Zhao

AAAI 2024 ProAgent: Building Proactive Cooperative Agents with Large Language Models Ceyao Zhang, Kaijie Yang, Siyi Hu, Zihao Wang, Guanghe Li, Yihang Sun, Cheng Zhang, Zhaowei Zhang, Anji Liu, Song-Chun Zhu, Xiaojun Chang, Junge Zhang, Feng Yin, Yitao Liang, Yaodong Yang

ICMLW 2024 ProxyTune: Hyperparameter Tuning Through Iteratively Refined Proxies Agrin Hilmkil, Wenbo Gong, Nick Pawlowski, Cheng Zhang

ICML 2024 Reflected Flow Matching Tianyu Xie, Yu Zhu, Longlin Yu, Tong Yang, Ziheng Cheng, Shiyue Zhang, Xiangyu Zhang, Cheng Zhang

CVPR 2024 Taming Stable Diffusion for Text to 360 Panorama Image Generation Cheng Zhang, Qianyi Wu, Camilo Cruz Gambardella, Xiaoshui Huang, Dinh Phung, Wanli Ouyang, Jianfei Cai

CVPR 2024 TextureDreamer: Image-Guided Texture Synthesis Through Geometry-Aware Diffusion Yu-Ying Yeh, Jia-Bin Huang, Changil Kim, Lei Xiao, Thu Nguyen-Phuoc, Numair Khan, Cheng Zhang, Manmohan Chandraker, Carl S Marshall, Zhao Dong, Zhengqin Li

ICML 2024 Towards Causal Foundation Model: On Duality Between Optimal Balancing and Attention Jiaqi Zhang, Joel Jennings, Agrin Hilmkil, Nick Pawlowski, Cheng Zhang, Chao Ma

CVPR 2024 Towards Effective Usage of Human-Centric Priors in Diffusion Models for Text-Based Human Image Generation Junyan Wang, Zhenhong Sun, Zhiyu Tan, Xuanbai Chen, Weihua Chen, Hao Li, Cheng Zhang, Yang Song

ICMLW 2024 Unlocking the Global Synergies in Low-Rank Adapters Zixi Zhang, Cheng Zhang, Xitong Gao, Robert D. Mullins, George Anthony Constantinides, Yiren Zhao

NeurIPS 2024 Visual Data Diagnosis and Debiasing with Concept Graphs Rwiddhi Chakraborty, Yinong Wang, Jialu Gao, Runkai Zheng, Cheng Zhang, Fernando De la Torre

NeurIPSW 2024 Zero-Shot Learning of Causal Models Divyat Mahajan, Jannes Gladrow, Agrin Hilmkil, Cheng Zhang, Meyer Scetbon

NeurIPS 2023 ARTree: A Deep Autoregressive Model for Phylogenetic Inference Tianyu Xie, Cheng Zhang

ICMLW 2023 Answering Causal Questions with Augmented LLMs Nick Pawlowski, James Vaughan, Joel Jennings, Cheng Zhang

NeurIPS 2023 BayesDAG: Gradient-Based Posterior Inference for Causal Discovery Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong

ICMLW 2023 BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong

ICML 2023 CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design Desi R. Ivanova, Joel Jennings, Tom Rainforth, Cheng Zhang, Adam Foster

ICLR 2023 Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang

CVPRW 2023 Efficient Deep Models for Real-Time 4k Image Super-Resolution. NTIRE 2023 Benchmark and Report Marcos V. Conde, Eduard Zamfir, Radu Timofte, Daniel Motilla, Cen Liu, Zexin Zhang, Yunbo Peng, Yue Lin, Jiaming Guo, Xueyi Zou, Yuyi Chen, Yi Liu, Jia Hao, Youliang Yan, Yuanfan Zhang, Gen Li, Lei Sun, Lingshun Kong, Haoran Bai, Jinshan Pan, Jiangxin Dong, Jinhui Tang, Mustafa Ayazoglu, Bahri Batuhan Bilecen, Mingxi Li, Yuhang Zhang, Xianjun Fan, Yankai Sheng, Long Sun, Zibin Liu, Weiran Gou, Shaoqing Li, Ziyao Yi, Yan Xiang, Dehui Kong, Ke Xu, Ganzorig Gankhuyag, Kihwan Yoon, Jin Zhang, Gaocheng Yu, Feng Zhang, Hongbin Wang, Zhou Zhou, Jiahao Chao, Hongfan Gao, Jiali Gong, Zhengfeng Yang, Zhenbing Zeng, Chengpeng Chen, Zichao Guo, Anjin Park, Yuqing Liu, Qi Jia, Hongyuan Yu, Xuanwu Yin, Dongyang Zhang, Ting Fu, Zhengxue Cheng, Shiai Zhu, Dajiang Zhou, Weichen Yu, Lin Ge, Jiahua Dong, Yajun Zou, Zhuoyuan Wu, Binnan Han, Xiaolin Zhang, Heng Zhang, Ben Shao, Shaolong Zheng, Daheng Yin, Baijun Chen, Mengyang Liu, Marian-Sergiu Nistor, Yi-Chung Chen, Zhi-Kai Huang, Yuan-Chun Chiang, Wei-Ting Chen, Hao-Hsiang Yang, Hua-En Chang, I-Hsiang Chen, Chia-Hsuan Hsieh, Sy-Yen Kuo, Tu Vo, Qingsen Yan, Yun Zhu, Jinqiu Su, Yanning Zhang, Cheng Zhang, Jiaying Luo, Youngsun Cho, Nakyung Lee, Kunlong Zuo

NeurIPS 2023 Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration Longlin Yu, Tianyu Xie, Yu Zhu, Tong Yang, Xiangyu Zhang, Cheng Zhang

NeurIPS 2023 High Precision Causal Model Evaluation with Conditional Randomization Chao Ma, Cheng Zhang

ICCV 2023 ITI-GEN: Inclusive Text-to-Image Generation Cheng Zhang, Xuanbai Chen, Siqi Chai, Chen Henry Wu, Dmitry Lagun, Thabo Beeler, Fernando De la Torre

TMLR 2023 Learn the Time to Learn: Replay Scheduling in Continual Learning Marcus Klasson, Hedvig Kjellstrom, Cheng Zhang

ICLR 2023 Learnable Topological Features for Phylogenetic Inference via Graph Neural Networks Cheng Zhang

ICCV 2023 Neural-PBIR Reconstruction of Shape, Material, and Illumination Cheng Sun, Guangyan Cai, Zhengqin Li, Kai Yan, Cheng Zhang, Carl Marshall, Jia-Bin Huang, Shuang Zhao, Zhao Dong

TMLR 2023 Optimistic Optimization of Gaussian Process Samples Julia Grosse, Cheng Zhang, Philipp Hennig

NeurIPS 2023 Particle-Based Variational Inference with Generalized Wasserstein Gradient Flow Ziheng Cheng, Shiyue Zhang, Longlin Yu, Cheng Zhang

ICLR 2023 Rhino: Deep Causal Temporal Relationship Learning with History-Dependent Noise Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski

ICMLW 2023 RustGen: An Augmentation Approach for Generating Compilable Rust Code with Large Language Models Xingbo Wu, Nathanaël Cheriere, Cheng Zhang, Dushyanth Narayanan

ICLR 2023 Semi-Implicit Variational Inference via Score Matching Longlin Yu, Cheng Zhang

CVPR 2023 TokenHPE: Learning Orientation Tokens for Efficient Head Pose Estimation via Transformers Cheng Zhang, Hai Liu, Yongjian Deng, Bochen Xie, Youfu Li

NeurIPSW 2022 A Causal AI Suite for Decision-Making Emre Kiciman, Eleanor Wiske Dillon, Darren Edge, Adam Foster, Agrin Hilmkil, Joel Jennings, Chao Ma, Robert Ness, Nick Pawlowski, Amit Sharma, Cheng Zhang

NeurIPSW 2022 Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang

NeurIPSW 2022 Deep End-to-End Causal Inference Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Agrin Hilmkil, Joel Jennings, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang

CVPR 2022 Exploring and Evaluating Image Restoration Potential in Dynamic Scenes Cheng Zhang, Shaolin Su, Yu Zhu, Qingsen Yan, Jinqiu Sun, Yanning Zhang

CVPR 2022 Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations Zirui Peng, Shaofeng Li, Guoxing Chen, Cheng Zhang, Haojin Zhu, Minhui Xue

ECCV 2022 Learning with Free Object Segments for Long-Tailed Instance Segmentation Cheng Zhang, Tai-Yu Pan, Tianle Chen, Jike Zhong, Wenjin Fu, Wei-Lun Chao

CLeaR 2022 Local Constraint-Based Causal Discovery Under Selection Bias Philip Versteeg, Joris Mooij, Cheng Zhang

ICLR 2022 Optimal Transport for Causal Discovery Ruibo Tu, Kun Zhang, Hedvig Kjellstrom, Cheng Zhang

CVPR 2022 PatchFormer: An Efficient Point Transformer with Patch Attention Cheng Zhang, Haocheng Wan, Xinyi Shen, Zizhao Wu

NeurIPSW 2022 Rhino: Deep Causal Temporal Relationship Learning with History-Dependent Noise Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski

NeurIPS 2022 Simultaneous Missing Value Imputation and Structure Learning with Groups Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang

AISTATS 2021 Meta-Learning Divergences for Variational Inference Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang

NeurIPSW 2021 Accurate Imputation and Efficient Data Acquisitionwith Transformer-Based VAEs Sarah Lewis, Tatiana Matejovicova, Yingzhen Li, Angus Lamb, Yordan Zaykov, Miltiadis Allamanis, Cheng Zhang

ICCVW 2021 Countering Adversarial Examples: Combining Input Transformation and Noisy Training Cheng Zhang, Pan Gao

ICCV 2021 DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context Graph and Relation-Based Optimization Cheng Zhang, Zhaopeng Cui, Cai Chen, Shuaicheng Liu, Bing Zeng, Hujun Bao, Yinda Zhang

ICMLW 2021 Defending Adversaries Using Unsupervised Feature Clustering VAE Cheng Zhang, Pan Gao

AAAI 2021 Educational Question Mining at Scale: Prediction, Analysis and Personalization Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Richard G. Baraniuk, Cheng Zhang

AAAI 2021 Estimating Α-Rank by Maximizing Information Gain Tabish Rashid, Cheng Zhang, Kamil Ciosek

CVPR 2021 Holistic 3D Scene Understanding from a Single Image with Implicit Representation Cheng Zhang, Zhaopeng Cui, Yinda Zhang, Bing Zeng, Marc Pollefeys, Shuaicheng Liu

NeurIPS 2021 Identifiable Generative Models for Missing Not at Random Data Imputation Chao Ma, Cheng Zhang

ICCV 2021 MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection Cheng Zhang, Tai-Yu Pan, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, Wei-Lun Chao

NeurIPS 2021 On Model Calibration for Long-Tailed Object Detection and Instance Segmentation Tai-Yu Pan, Cheng Zhang, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, Wei-Lun Chao

UAI 2021 Probabilistic DAG Search Julia Grosse, Cheng Zhang, Philipp Hennig

NeurIPS 2021 Sparse Uncertainty Representation in Deep Learning with Inducing Weights Hippolyt Ritter, Martin Kukla, Cheng Zhang, Yingzhen Li

NeurIPS 2020 A Causal View on Robustness of Neural Networks Cheng Zhang, Kun Zhang, Yingzhen Li

ICLR 2020 AMRL: Aggregated Memory for Reinforcement Learning Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann

ICMLW 2020 Causal Discovery in the Presence of Missing Values for Neuropathic Pain Diagnosis Ruibo Tu, Kun Zhang, Bo Christer Bertilson, Clark Glymour, Hedvig Kjellström, Cheng Zhang

NeurIPS 2020 How Do Fair Decisions Fare in Long-Term Qualification? Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellstrom, Kun Zhang, Cheng Zhang

NeurIPS 2020 Improved Variational Bayesian Phylogenetic Inference with Normalizing Flows Cheng Zhang

AAAI 2020 Learning from Easy to Complex: Adaptive Multi-Curricula Learning for Neural Dialogue Generation Hengyi Cai, Hongshen Chen, Cheng Zhang, Yonghao Song, Xiaofang Zhao, Yangxi Li, Dongsheng Duan, Dawei Yin

NeurIPSW 2020 Reinforcement Learning with Efficient Active Feature Acquisition Haiyan Yin, Yingzhen Li, Sinno Pan, Cheng Zhang, Sebastian Tschiatschek

NeurIPS 2020 VAEM: A Deep Generative Model for Heterogeneous Mixed Type Data Chao Ma, Sebastian Tschiatschek, Richard Turner, José Miguel Hernández-Lobato, Cheng Zhang

ICMLW 2020 VAEM: A Deep Generative Model for Heterogeneous Mixed Type Data Chao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang

AAAI 2020 Weakly-Supervised Fine-Grained Event Recognition on Social Media Texts for Disaster Management Wenlin Yao, Cheng Zhang, Shiva Saravanan, Ruihong Huang, Ali Mostafavi

WACV 2019 A Hierarchical Grocery Store Image Dataset with Visual and Semantic Labels Marcus Klasson, Cheng Zhang, Hedvig Kjellström

AAAI 2019 Active Mini-Batch Sampling Using Repulsive Point Processes Cheng Zhang, Cengiz Öztireli, Stephan Mandt, Giampiero Salvi

AISTATS 2019 Causal Discovery in the Presence of Missing Data Ruibo Tu, Cheng Zhang, Paul Ackermann, Karthika Mohan, Hedvig Kjellström, Kun Zhang

ICML 2019 EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE Chao Ma, Sebastian Tschiatschek, Konstantina Palla, Jose Miguel Hernandez-Lobato, Sebastian Nowozin, Cheng Zhang

NeurIPS 2019 Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann

NeurIPS 2019 Icebreaker: Element-Wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model Wenbo Gong, Sebastian Tschiatschek, Sebastian Nowozin, Richard E Turner, José Miguel Hernández-Lobato, Cheng Zhang

NeurIPS 2019 Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation Ruibo Tu, Kun Zhang, Bo Bertilson, Hedvig Kjellstrom, Cheng Zhang

MLHC 2019 Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation Charles Hamesse, Ruibo Tu, Paul Ackermann, Hedvig Kjellström, Cheng Zhang

ICLR 2019 Variational Bayesian Phylogenetic Inference Cheng Zhang, Frederick A. Matsen Iv

AAAI 2018 An Ant-Based Algorithm to Solve Distributed Constraint Optimization Problems Ziyu Chen, Tengfei Wu, Yanchen Deng, Cheng Zhang

AAAI 2018 Emphasizing 3D Properties in Recurrent Multi-View Aggregation for 3D Shape Retrieval Cheng Xu, Biao Leng, Cheng Zhang, Xiaochen Zhou

NeurIPS 2018 Generalizing Tree Probability Estimation via Bayesian Networks Cheng Zhang, Frederick A Matsen Iv

IJCAI 2018 Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation Charles Hamesse, Hedvig Kjellström, Paul Ackermann, Cheng Zhang

UAI 2017 Balanced Mini-Batch Sampling for SGD Using Determinantal Point Processes Cheng Zhang, Hedvig Kjellström, Stephan Mandt

NeurIPS 2017 Perturbative Black Box Variational Inference Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt

ICML 2017 Probabilistic Path Hamiltonian Monte Carlo Vu Dinh, Arman Bilge, Cheng Zhang, Frederick A. Matsen IV

MLHC 2016 Diagnostic Prediction Using Discomfort Drawings with IBTM Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek, Bo Bertilson

ECCV 2016 Inter-Battery Topic Representation Learning Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek

ECCVW 2014 How to Supervise Topic Models Cheng Zhang, Hedvig Kjellström

ICLR 2013 Factorized Topic Models Cheng Zhang, Carl Henrik Ek, Hedvig Kjellström

ICCVW 2013 Supervised Hierarchical Dirichlet Processes with Variational Inference Cheng Zhang, Carl Henrik Ek, Xavi Gratal, Florian T. Pokorny, Hedvig Kjellström

AAAI 2010 G-Optimal Design with Laplacian Regularization Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, Lijun Zhang, Cheng Zhang