Yongxin Chen
33 papers · 2019–2026 · 9 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (15) π§ Keyword Pioneer π Interdisciplinary Bridge π Renaissance Researcher (5) π Conference Polyglot (8)
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Conference Polyglot
(8)
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Academic Marathon
(6)
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Cross-Pollinator
(13)
π
Grand Slam
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Triple Crown
π€
Dynamic Duo
(11)
β‘
Prolific Year
(5)
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Conference Pioneer
ποΈ
Keyword Collector
(94)
π₯
Unstoppable
(7)
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Century Club
(32)
β
The Questioner
Conferences
ICLR (8)
NIPS (7)
ICML (4)
COLT (3)
CORL (3)
L4DC (3)
AISTATS (2)
CVPR (2)
AAAI (1)
Top co-authors
Keywords
diffusion model
(7)
reinforcement learning
(3)
optimal transport
(3)
image generation
(3)
policy gradient
(2)
wasserstein barycenter
(2)
generative model
(2)
distributional reinforcement learning
(2)
probability distribution
(2)
log-concave distribution
(2)
temporal difference learning
(1)
variational inference
(1)
convex optimization
(1)
imitation learning
(1)
sample efficiency
(1)
neural tangent kernel
(1)
attention mechanism
(1)
few-shot learning
(1)
stochastic gradient descent
(1)
video generation
(1)
Papers
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
Joint Model-based Model-free Diffusion for Planning with Constraints
CORL 2025
Proximal Sampler with Adaptive Step Size
AISTATS 2025
Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling
ICLR 2025
Improving Neural Optimal Transport via Displacement Interpolation
ICLR 2025
Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling
ICLR 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
Generative Factor Chaining: Coordinated Manipulation with Diffusion-based Factor Graph
CORL 2024
Toward effective protection against diffusion-based mimicry through score distillation
ICLR 2024
QueST: Self-Supervised Skill Abstractions for Learning Continuous Control
NIPS 2024
RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance
NIPS 2024
Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policies
NIPS 2024
On a Class of Gibbs Sampling over Networks
COLT 2023
DiffCollage: Parallel Generation of Large Content With Diffusion Models
CVPR 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
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability
NIPS 2023
Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation
ICML 2023
Improved dimension dependence of a proximal algorithm for sampling
COLT 2023
On the complexity of the optimal transport problem with graph-structured cost
AISTATS 2022
Sample-based Distributional Policy Gradient
L4DC 2022
Variational Wasserstein gradient flow
ICML 2022
Path Integral Sampler: A Stochastic Control Approach For Sampling
ICLR 2022
Improved analysis for a proximal algorithm for sampling
COLT 2022
Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
ICML 2021
Diffusion Normalizing Flow
NIPS 2021
Can Temporal-Diο¬erence and Q-Learning Learn Representation? A Mean-Field Theory
NIPS 2020
Improving Robustness via Risk Averse Distributional Reinforcement Learning
L4DC 2020
Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games
ICLR 2020
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost
NIPS 2019