Chen, Yongxin

46 publications

NeurIPS 2025 Adjoint Schrödinger Bridge Sampler Guan-Horng Liu, Jaemoo Choi, Yongxin Chen, Benjamin Kurt Miller, Ricky T. Q. Chen

CVPR 2025 Articulated Kinematics Distillation from Video Diffusion Models Xuan Li, Qianli Ma, Tsung-Yi Lin, Yongxin Chen, Chenfanfu Jiang, Ming-Yu Liu, Donglai Xiang

TMLR 2025 Client-Only Distributed Markov Chain Monte Carlo Sampling over a Network Bo Yuan, Jiaojiao Fan, Jiaming Liang, Yongxin Chen

ICLRW 2025 Complexity Analysis of Normalizing Constant Estimation: From Jarzynski Equality to Annealed Importance Sampling and Beyond Wei Guo, Molei Tao, Yongxin Chen

ICML 2025 Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model Is Secretly a GAN Discriminator Kaiwen Zheng, Yongxin Chen, Huayu Chen, Guande He, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang

NeurIPS 2025 Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms Yinuo Ren, Haoxuan Chen, Yuchen Zhu, Wei Guo, Yongxin Chen, Grant M. Rotskoff, Molei Tao, Lexing Ying

ICLRW 2025 Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms Yinuo Ren, Haoxuan Chen, Yuchen Zhu, Wei Guo, Yongxin Chen, Grant M. Rotskoff, Molei Tao, Lexing Ying

L4DC 2025 Flow Matching for Stochastic Linear Control Systems Yuhang Mei, Mohammad Al-Jarrah, Amirhossein Taghvaei, Yongxin Chen

ICLR 2025 Improving Neural Optimal Transport via Displacement Interpolation Jaemoo Choi, Yongxin Chen, Jaewoong Choi

CoRL 2025 Joint Model-Based Model-Free Diffusion for Planning with Constraints Wonsuhk Jung, Utkarsh Aashu Mishra, Nadun Ranawaka Arachchige, Yongxin Chen, Danfei Xu, Shreyas Kousik

NeurIPS 2025 MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control Yuchen Zhu, Wei Guo, Jaemoo Choi, Guan-Horng Liu, Yongxin Chen, Molei Tao

ICLR 2025 Masked Diffusion Models Are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling Kaiwen Zheng, Yongxin Chen, Hanzi Mao, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang

NeurIPS 2025 Non-Equilibrium Annealed Adjoint Sampler Jaemoo Choi, Yongxin Chen, Molei Tao, Guan-Horng Liu

ICLR 2025 Provable Benefit of Annealed Langevin Monte Carlo for Non-Log-Concave Sampling Wei Guo, Molei Tao, Yongxin Chen

AISTATS 2025 Proximal Sampler with Adaptive Step Size Bo Yuan, Jiaojiao Fan, Jiaming Liang, Yongxin Chen

NeurIPS 2024 Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-Based Policies Yipu Chen, Haotian Xue, Yongxin Chen

CoRL 2024 Generative Factor Chaining: Coordinated Manipulation with Diffusion-Based Factor Graph Utkarsh Aashu Mishra, Yongxin Chen, Danfei Xu

NeurIPS 2024 QueST: Self-Supervised Skill Abstractions for Learning Continuous Control Atharva Mete, Haotian Xue, Albert Wilcox, Yongxin Chen, Animesh Garg

NeurIPS 2024 RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance Jiaojiao Fan, Haotian Xue, Qinsheng Zhang, Yongxin Chen

NeurIPSW 2024 Rethinking Adversarial Attacks as Protection Against Diffusion-Based Mimicry Haotian Xue, Yongxin Chen

ICLR 2024 Toward Effective Protection Against Diffusion-Based Mimicry Through Score Distillation Haotian Xue, Chumeng Liang, Xiaoyu Wu, Yongxin Chen

TMLR 2023 A Proximal Algorithm for Sampling Jiaming Liang, Yongxin Chen

CVPR 2023 DiffCollage: Parallel Generation of Large Content with Diffusion Models Qinsheng Zhang, Jiaming Song, Xun Huang, Yongxin Chen, Ming-Yu Liu

NeurIPS 2023 Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability Haotian Xue, Alexandre Araujo, Bin Hu, Yongxin Chen

ICLR 2023 Fast Sampling of Diffusion Models with Exponential Integrator Qinsheng Zhang, Yongxin Chen

CoRL 2023 Generative Skill Chaining: Long-Horizon Skill Planning with Diffusion Models Utkarsh Aashu Mishra, Shangjie Xue, Yongxin Chen, Danfei Xu

COLT 2023 Improved Dimension Dependence of a Proximal Algorithm for Sampling Jiaojiao Fan, Bo Yuan, Yongxin Chen

ICML 2023 Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation Jiaming Song, Qinsheng Zhang, Hongxu Yin, Morteza Mardani, Ming-Yu Liu, Jan Kautz, Yongxin Chen, Arash Vahdat

TMLR 2023 Neural Monge mAP Estimation and Its Applications Jiaojiao Fan, Shu Liu, Shaojun Ma, Hao-Min Zhou, Yongxin Chen

COLT 2023 On a Class of Gibbs Sampling over Networks Bo Yuan, Jiaojiao Fan, Jiaming Liang, Andre Wibisono, Yongxin Chen

TMLR 2023 Signed Graph Neural Networks: A Frequency Perspective Rahul Singh, Yongxin Chen

ICLR 2023 gDDIM: Generalized Denoising Diffusion Implicit Models Qinsheng Zhang, Molei Tao, Yongxin Chen

AISTATS 2022 On the Complexity of the Optimal Transport Problem with Graph-Structured Cost Jiaojiao Fan, Isabel Haasler, Johan Karlsson, Yongxin Chen

NeurIPSW 2022 AsymQ: Asymmetric Q-Loss to Mitigate Overestimation Bias in Off-Policy Reinforcement Learning Qinsheng Zhang, Arjun Krishna, Sehoon Ha, Yongxin Chen

NeurIPSW 2022 Fast Sampling of Diffusion Models with Exponential Integrator Qinsheng Zhang, Yongxin Chen

COLT 2022 Improved Analysis for a Proximal Algorithm for Sampling Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono

ICLR 2022 Path Integral Sampler: A Stochastic Control Approach for Sampling Qinsheng Zhang, Yongxin Chen

L4DC 2022 Sample-Based Distributional Policy Gradient Rahul Singh, Keuntaek Lee, Yongxin Chen

ICLRW 2022 Scalable Computation of Monge Maps with General Costs Jiaojiao Fan, Shu Liu, Shaojun Ma, Yongxin Chen, Hao-Min Zhou

ICML 2022 Variational Wasserstein Gradient Flow Jiaojiao Fan, Qinsheng Zhang, Amirhossein Taghvaei, Yongxin Chen

NeurIPS 2021 Diffusion Normalizing Flow Qinsheng Zhang, Yongxin Chen

ICML 2021 Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks Jiaojiao Fan, Amirhossein Taghvaei, Yongxin Chen

ICLR 2020 Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games Zuyue Fu, Zhuoran Yang, Yongxin Chen, Zhaoran Wang

NeurIPS 2020 Can Temporal-Diﬀerence and Q-Learning Learn Representation? a Mean-Field Theory Yufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang

L4DC 2020 Improving Robustness via Risk Averse Distributional Reinforcement Learning Rahul Singh, Qinsheng Zhang, Yongxin Chen

NeurIPS 2019 Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost Zhuoran Yang, Yongxin Chen, Mingyi Hong, Zhaoran Wang