Chen, Changyou

84 publications

WACV 2025 Cross-Modal Feature Alignment and MMD Improve Robustness of Prompt Tuning Jingchen Sun, Rohan Sharma, Vishnu Lokhande, Changyou Chen

WACV 2025 Long-Term Ad Memorability: Understanding & Generating Memorable Ads Harini Si, Somesh Singh, Yaman Kumar Singla, Aanisha Bhattacharyya, Veeky Baths, Changyou Chen, Rajiv Ratn Shah, Balaji Krishnamurthy

ICLR 2025 Measuring and Improving Engagement of Text-to-Image Generation Models Varun Khurana, Yaman Kumar Singla, Jayakumar Subramanian, Changyou Chen, Rajiv Ratn Shah, Zhiqiang Xu, Balaji Krishnamurthy

ICCV 2025 Multi-Modal Multi-Task Unified Embedding Model (M3T-UEM): A Task-Adaptive Representation Learning Framework Rohan Sharma, Changyou Chen, Feng-Ju Chang, Seongjun Yun, Xiaohu Xie, Rui Meng, Dehong Xu, Alejandro Mottini, Qingjun Cui

ICCV 2025 Multimodal LLMs as Customized Reward Models for Text-to-Image Generation Shijie Zhou, Ruiyi Zhang, Huaisheng Zhu, Branislav Kveton, Yufan Zhou, Jiuxiang Gu, Jian Chen, Changyou Chen

NeurIPS 2025 SPRO: Improving Image Generation via Self-Play Ritika Jha, Aanisha Bhattacharyya, Yaman Kumar Singla, Rajiv Ratn Shah, Changyou Chen, Balaji Krishnamurthy

ICLR 2025 SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding Jian Chen, Ruiyi Zhang, Yufan Zhou, Tong Yu, Franck Dernoncourt, Jiuxiang Gu, Ryan A. Rossi, Changyou Chen, Tong Sun

ICLR 2025 Teaching Human Behavior Improves Content Understanding Abilities of VLMs Somesh Kumar Singh, S I Harini, Yaman Kumar Singla, Changyou Chen, Rajiv Ratn Shah, Veeky Baths, Balaji Krishnamurthy

TMLR 2025 Understanding Fine-Tuning in Approximate Unlearning: A Theoretical Perspective Meng Ding, Rohan Sharma, Changyou Chen, Jinhui Xu, Kaiyi Ji

ICLRW 2025 VisR-Bench: A Visual Retrieval Benchmark for Visually-Rich Documents Jian Chen, Ruiyi Zhang, Ming Li, Shijie Zhou, Changyou Chen

NeurIPS 2024 A Probability Contrastive Learning Framework for 3D Molecular Representation Learning Jiayu Qin, Jian Chen, Rohan Sharma, Jingchen Sun, Changyou Chen

ICLR 2024 AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning Rohan Sharma, Kaiyi Ji, Zhiqiang Xu, Changyou Chen

ICLR 2024 Diffusion Models for Multi-Task Generative Modeling Changyou Chen, Han Ding, Bunyamin Sisman, Yi Xu, Ouye Xie, Benjamin Z. Yao, Son Dinh Tran, Belinda Zeng

ICLR 2024 Large Content and Behavior Models to Understand, Simulate, and Optimize Content and Behavior Ashmit Khandelwal, Aditya Agrawal, Aanisha Bhattacharyya, Yaman Kumar, Somesh Singh, Uttaran Bhattacharya, Ishita Dasgupta, Stefano Petrangeli, Rajiv Ratn Shah, Changyou Chen, Balaji Krishnamurthy

CVPR 2024 TRINS: Towards Multimodal Language Models That Can Read Ruiyi Zhang, Yanzhe Zhang, Jian Chen, Yufan Zhou, Jiuxiang Gu, Changyou Chen, Tong Sun

ICLR 2024 Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints Jian Chen, Ruiyi Zhang, Yufan Zhou, Changyou Chen

AAAI 2023 AUC Maximization for Low-Resource Named Entity Recognition Ngoc Dang Nguyen, Wei Tan, Lan Du, Wray L. Buntine, Richard Beare, Changyou Chen

ICML 2023 Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction Jianyi Zhang, Ang Li, Minxue Tang, Jingwei Sun, Xiang Chen, Fan Zhang, Changyou Chen, Yiran Chen, Hai Li

NeurIPS 2023 Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels Jian Chen, Ruiyi Zhang, Tong Yu, Rohan Sharma, Zhiqiang Xu, Tong Sun, Changyou Chen

ICML 2023 Learning Unnormalized Statistical Models via Compositional Optimization Wei Jiang, Jiayu Qin, Lingyu Wu, Changyou Chen, Tianbao Yang, Lijun Zhang

AAAI 2023 Persuasion Strategies in Advertisements Yaman Kumar, Rajat Jha, Arunim Gupta, Milan Aggarwal, Aditya Garg, Tushar Malyan, Ayush Bhardwaj, Rajiv Ratn Shah, Balaji Krishnamurthy, Changyou Chen

CVPR 2023 Shifted Diffusion for Text-to-Image Generation Yufan Zhou, Bingchen Liu, Yizhe Zhu, Xiao Yang, Changyou Chen, Jinhui Xu

CVPR 2023 Understanding and Constructing Latent Modality Structures in Multi-Modal Representation Learning Qian Jiang, Changyou Chen, Han Zhao, Liqun Chen, Qing Ping, Son Dinh Tran, Yi Xu, Belinda Zeng, Trishul Chilimbi

AAAI 2022 MINIMAL: Mining Models for Universal Adversarial Triggers Yaman Kumar Singla, Swapnil Parekh, Somesh Singh, Changyou Chen, Balaji Krishnamurthy, Rajiv Ratn Shah

CVPR 2022 Rethinking Deep Face Restoration Yang Zhao, Yu-Chuan Su, Chun-Te Chu, Yandong Li, Marius Renn, Yukun Zhu, Changyou Chen, Xuhui Jia

AAAI 2022 TiGAN: Text-Based Interactive Image Generation and Manipulation Yufan Zhou, Ruiyi Zhang, Jiuxiang Gu, Chris Tensmeyer, Tong Yu, Changyou Chen, Jinhui Xu, Tong Sun

CVPR 2022 Towards Language-Free Training for Text-to-Image Generation Yufan Zhou, Ruiyi Zhang, Changyou Chen, Chunyuan Li, Chris Tensmeyer, Tong Yu, Jiuxiang Gu, Jinhui Xu, Tong Sun

AAAI 2022 Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees Yaman Kumar Singla, Sriram Krishna, Rajiv Ratn Shah, Changyou Chen

NeurIPS 2022 Why Do We Need Large Batchsizes in Contrastive Learning? a Gradient-Bias Perspective Changyou Chen, Jianyi Zhang, Yi Xu, Liqun Chen, Jiali Duan, Yiran Chen, Son Tran, Belinda Zeng, Trishul Chilimbi

ICLR 2021 Meta-Learning with Neural Tangent Kernels Yufan Zhou, Zhenyi Wang, Jiayi Xian, Changyou Chen, Jinhui Xu

ICLR 2021 MixKD: Towards Efficient Distillation of Large-Scale Language Models Kevin J Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin

CVPRW 2021 ReMP: Rectified Metric Propagation for Few-Shot Learning Yang Zhao, Chunyuan Li, Ping Yu, Changyou Chen

CVPRW 2021 Towards Fair Federated Learning with Zero-Shot Data Augmentation Weituo Hao, Mostafa El-Khamy, Jungwon Lee, Jianyi Zhang, Kevin J. Liang, Changyou Chen, Lawrence Carin

CVPR 2021 Unpaired Image-to-Image Translation via Latent Energy Transport Yang Zhao, Changyou Chen

IJCAI 2021 Unsupervised Hashing with Contrastive Information Bottleneck Zexuan Qiu, Qinliang Su, Zijing Ou, Jianxing Yu, Changyou Chen

ICLR 2020 Bayesian Meta Sampling for Fast Uncertainty Adaptation Zhenyi Wang, Yang Zhao, Ping Yu, Ruiyi Zhang, Changyou Chen

NeurIPS 2020 Bayesian Multi-Type Mean Field Multi-Agent Imitation Learning Fan Yang, Alina Vereshchaka, Changyou Chen, Wen Dong

ICLR 2020 Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson

ICML 2020 Feature Quantization Improves GAN Training Yang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen

AAAI 2020 Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions Zhenyi Wang, Ping Yu, Yang Zhao, Ruiyi Zhang, Yufan Zhou, Junsong Yuan, Changyou Chen

NeurIPS 2020 Learning Manifold Implicitly via Explicit Heat-Kernel Learning Yufan Zhou, Changyou Chen, Jinhui Xu

AISTATS 2020 Nested-Wasserstein Self-Imitation Learning for Sequence Generation Ruiyi Zhang, Changyou Chen, Zhe Gan, Zheng Wen, Wenlin Wang, Lawrence Carin

AISTATS 2020 Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang, Ruiyi Zhang, Lawrence Carin, Changyou Chen

ECCV 2020 Structure-Aware Human-Action Generation Ping Yu, Yang Zhao, Chunyuan Li, Junsong Yuan, Changyou Chen

ICML 2020 Variance Reduction in Stochastic Particle-Optimization Sampling Jianyi Zhang, Yang Zhao, Changyou Chen

AAAI 2020 Variational Adversarial Kernel Learned Imitation Learning Fan Yang, Alina Vereshchaka, Yufan Zhou, Changyou Chen, Wen Dong

AISTATS 2019 Adversarial Learning of a Sampler Based on an Unnormalized Distribution Chunyuan Li, Ke Bai, Jianqiao Li, Guoyin Wang, Changyou Chen, Lawrence Carin

IJCAI 2019 Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Jun Wen, Nenggan Zheng, Junsong Yuan, Zhefeng Gong, Changyou Chen

NeurIPS 2019 Certified Adversarial Robustness with Additive Noise Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin

AAAI 2019 Communication-Efficient Stochastic Gradient MCMC for Neural Networks Chunyuan Li, Changyou Chen, Yunchen Pu, Ricardo Henao, Lawrence Carin

IJCAI 2019 Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm Mengdi Huai, Hongfei Xue, Chenglin Miao, Liuyi Yao, Lu Su, Changyou Chen, Aidong Zhang

ICML 2019 Differentially Private Empirical Risk Minimization with Non-Convex Loss Functions Di Wang, Changyou Chen, Jinhui Xu

AAAI 2019 Distributionally Adversarial Attack Tianhang Zheng, Changyou Chen, Kui Ren

ICLR 2019 Improving Sequence-to-Sequence Learning via Optimal Transport Liqun Chen, Yizhe Zhang, Ruiyi Zhang, Chenyang Tao, Zhe Gan, Haichao Zhang, Bai Li, Dinghan Shen, Changyou Chen, Lawrence Carin

AISTATS 2019 On Connecting Stochastic Gradient MCMC and Differential Privacy Bai Li, Changyou Chen, Hao Liu, Lawrence Carin

AISTATS 2019 Scalable Thompson Sampling via Optimal Transport Ruiyi Zhang, Zheng Wen, Changyou Chen, Chen Fang, Tong Yu, Lawrence Carin

AAAI 2019 Self-Adversarially Learned Bayesian Sampling Yang Zhao, Jianyi Zhang, Changyou Chen

NeurIPS 2019 Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin, Changyou Chen

UAI 2018 A Unified Particle-Optimization Framework for Scalable Bayesian Sampling Changyou Chen, Ruiyi Zhang, Wenlin Wang, Bai Li, Liqun Chen

ICML 2018 Continuous-Time Flows for Efficient Inference and Density Estimation Changyou Chen, Chunyuan Li, Liqun Chen, Wenlin Wang, Yunchen Pu, Lawrence Carin Duke

AISTATS 2018 Learning Structural Weight Uncertainty for Sequential Decision-Making Ruiyi Zhang, Chunyuan Li, Changyou Chen, Lawrence Carin

ICML 2018 Policy Optimization as Wasserstein Gradient Flows Ruiyi Zhang, Changyou Chen, Chunyuan Li, Lawrence Carin

AISTATS 2018 Symmetric Variational Autoencoder and Connections to Adversarial Learning Liqun Chen, Shuyang Dai, Yunchen Pu, Erjin Zhou, Chunyuan Li, Qinliang Su, Changyou Chen, Lawrence Carin

AAAI 2018 Zero-Shot Learning via Class-Conditioned Deep Generative Models Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin

NeurIPS 2017 ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching Chunyuan Li, Hao Liu, Changyou Chen, Yuchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin

AISTATS 2017 Learning Structured Weight Uncertainty in Bayesian Neural Networks Shengyang Sun, Changyou Chen, Lawrence Carin

ICML 2017 Stochastic Gradient Monomial Gamma Sampler Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin

AISTATS 2016 Bridging the Gap Between Stochastic Gradient MCMC and Stochastic Optimization Changyou Chen, David E. Carlson, Zhe Gan, Chunyuan Li, Lawrence Carin

ECML-PKDD 2016 Deep Metric Learning with Data Summarization Wenlin Wang, Changyou Chen, Wenlin Chen, Piyush Rai, Lawrence Carin

AAAI 2016 High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models Chunyuan Li, Changyou Chen, Kai Fan, Lawrence Carin

ECML-PKDD 2016 Laplacian Hamiltonian Monte Carlo Yizhe Zhang, Changyou Chen, Ricardo Henao, Lawrence Carin

CVPR 2016 Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification Chunyuan Li, Andrew Stevens, Changyou Chen, Yunchen Pu, Zhe Gan, Lawrence Carin

ICML 2016 Nonlinear Statistical Learning with Truncated Gaussian Graphical Models Qinliang Su, Xuejun Liao, Changyou Chen, Lawrence Carin

AAAI 2016 Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li, Changyou Chen, David E. Carlson, Lawrence Carin

NeurIPS 2016 Stochastic Gradient MCMC with Stale Gradients Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin

NeurIPS 2016 Towards Unifying Hamiltonian Monte Carlo and Slice Sampling Yizhe Zhang, Xiangyu Wang, Changyou Chen, Ricardo Henao, Kai Fan, Lawrence Carin

NeurIPS 2015 On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen, Nan Ding, Lawrence Carin

ECML-PKDD 2015 Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin

ICML 2015 Scalable Deep Poisson Factor Analysis for Topic Modeling Zhe Gan, Changyou Chen, Ricardo Henao, David Carlson, Lawrence Carin

NeurIPS 2014 Bayesian Sampling Using Stochastic Gradient Thermostats Nan Ding, Youhan Fang, Ryan Babbush, Changyou Chen, Robert D Skeel, Hartmut Neven

NeurIPS 2014 Robust Bayesian Max-Margin Clustering Changyou Chen, Jun Zhu, Xinhua Zhang

ICML 2013 Dependent Normalized Random Measures Changyou Chen, Vinayak Rao, Wray Buntine, Yee Whye Teh

ICML 2012 Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling Changyou Chen, Nan Ding, Wray L. Buntine

ECML-PKDD 2011 Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process Changyou Chen, Lan Du, Wray L. Buntine