Yongxin Chen

S-D-RSM: Stochastic Distributed Regularized Splitting Method for Large-Scale Convex Optimization Problems AAAI 2026 Articulated Kinematics Distillation from Video Diffusion Models CVPR 2025 Cross-attention and Self-attention for Audio-visual Speaker Diarization in MISP-Meeting Challenge Interspeech 2025 Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator ICML 2025 Flow matching for stochastic linear control systems L4DC 2025 Improving Neural Optimal Transport via Displacement Interpolation ICLR 2025 Joint Model-based Model-free Diffusion for Planning with Constraints CoRL 2025 Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling ICLR 2025 Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling ICLR 2025 Proximal Sampler with Adaptive Step Size AISTATS 2025 Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policies NeurIPS 2024 Generative Factor Chaining: Coordinated Manipulation with Diffusion-based Factor Graph CoRL 2024 QueST: Self-Supervised Skill Abstractions for Learning Continuous Control NeurIPS 2024 RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance NeurIPS 2024 Toward effective protection against diffusion-based mimicry through score distillation ICLR 2024 DiffCollage: Parallel Generation of Large Content With Diffusion Models CVPR 2023 Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability NeurIPS 2023 Fast Sampling of Diffusion Models with Exponential Integrator ICLR 2023 gDDIM: Generalized denoising diffusion implicit models ICLR 2023 Generative Skill Chaining: Long-Horizon Skill Planning with Diffusion Models CoRL 2023 Improved dimension dependence of a proximal algorithm for sampling COLT 2023 Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation ICML 2023 On a Class of Gibbs Sampling over Networks COLT 2023 Improved analysis for a proximal algorithm for sampling COLT 2022 On the complexity of the optimal transport problem with graph-structured cost AISTATS 2022 Path Integral Sampler: A Stochastic Control Approach For Sampling ICLR 2022 Sample-based Distributional Policy Gradient L4DC 2022 Variational Wasserstein gradient flow ICML 2022 Diffusion Normalizing Flow NeurIPS 2021 Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks ICML 2021 Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games ICLR 2020 Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory NeurIPS 2020 Improving Robustness via Risk Averse Distributional Reinforcement Learning L4DC 2020 Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost NeurIPS 2019