Yinuo Ren

25 papers A* 3A 3Journal 17Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Shrinkage matters: evidence from accuracy-diversity trade-off in regression ensembles.
Inf. Fusion
Han Feng, Pengyang Song, Yinuo Ren, Hanfeng Zhou, Jue Wang
2025 J jnl
A Unified Approach to Analysis and Design of Denoising Markov Models.
CoRR
Yinuo Ren, Grant M. Rotskoff, Lexing Ying
2025 A conf
COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework.
UAI
Yinuo Ren, Tesi Xiao, Michael Shavlovsky, Lexing Ying, Holakou Rahmanian
2025 J jnl
DriftLite: Lightweight Drift Control for Inference-Time Scaling of Diffusion Models.
CoRR
Yinuo Ren, Wenhao Gao, Lexing Ying, Grant M. Rotskoff, Jiequn Han
2025 J jnl
Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms.
CoRR
Yinuo Ren, Haoxuan Chen, Yuchen Zhu, Wei Guo, Yongxin Chen, Grant M. Rotskoff, Molei Tao, Lexing Ying
2025 A* conf
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework.
ICLR
Yinuo Ren, Haoxuan Chen, Grant M. Rotskoff, Lexing Ying
2025 J jnl
Optimal starting point for time series forecasting.
Expert Syst. Appl.
Yiming Zhong, Yinuo Ren, Guangyao Cao, Feng Li, Haobo Qi
2025 J jnl
Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach.
CoRR
Haoxuan Chen, Yinuo Ren, Martin Renqiang Min, Lexing Ying, Zachary Izzo
2024 A* conf
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity.
NeurIPS
Haoxuan Chen, Yinuo Ren, Lexing Ying, Grant M. Rotskoff
2024 J jnl
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity.
CoRR
Haoxuan Chen, Yinuo Ren, Lexing Ying, Grant M. Rotskoff
2024 J jnl
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework.
CoRR
Yinuo Ren, Haoxuan Chen, Grant M. Rotskoff, Lexing Ying
2024 J jnl
HyperDPO: Hypernetwork-based Multi-Objective Fine-Tuning Framework.
CoRR
Yinuo Ren, Tesi Xiao, Michael Shavlovsky, Lexing Ying, Holakou Rahmanian
2024 A conf
Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient Flow.
AISTATS
Yinuo Ren, Tesi Xiao, Tanmay Gangwani, Anshuka Rangi, Holakou Rahmanian, Lexing Ying, Subhajit Sanyal
2024 J jnl
Optimal starting point for time series forecasting.
CoRR
Yiming Zhong, Yinuo Ren, Guangyao Cao, Feng Li, Haobo Qi
2024 A* conf
Statistical Spatially Inhomogeneous Diffusion Inference.
AAAI
Yinuo Ren, Yiping Lu, Lexing Ying, Grant M. Rotskoff
2024 A conf
Understanding the Generalization Benefits of Late Learning Rate Decay.
AISTATS
Yinuo Ren, Chao Ma, Lexing Ying
2024 J jnl
Understanding the Generalization Benefits of Late Learning Rate Decay.
CoRR
Yinuo Ren, Chao Ma, Lexing Ying
2023 — conf
Infinite forecast combinations based on Dirichlet process.
ICDM (Workshops)
Yinuo Ren, Feng Li, Yanfei Kang, Jue Wang
2023 J jnl
Infinite forecast combinations based on Dirichlet process.
CoRR
Yinuo Ren, Feng Li, Yanfei Kang, Jue Wang
2023 J jnl
Multi-Objective Optimization via Wasserstein-Fisher-Rao Gradient Flow.
CoRR
Yinuo Ren, Tesi Xiao, Tanmay Gangwani, Anshuka Rangi, Holakou Rahmanian, Lexing Ying, Subhajit Sanyal
2023 J jnl
Statistical Spatially Inhomogeneous Diffusion Inference.
CoRR
Yinuo Ren, Yiping Lu, Lexing Ying, Grant M. Rotskoff
2022 J jnl
High-dimensional density estimation with tensorizing flow.
CoRR
Yinuo Ren, Hongli Zhao, Yuehaw Khoo, Lexing Ying
2021 — conf
A semigroup method for high dimensional committor functions based on neural network.
MSML
Haoya Li, Yuehaw Khoo, Yinuo Ren, Lexing Ying
2021 J jnl
Hermite spectral method for Fokker-Planck-Landau equation modeling collisional plasma.
J. Comput. Phys.
Ruo Li, Yinuo Ren, Yanli Wang
2020 J jnl
Solving for high dimensional committor functions using neural network with online approximation to derivatives.
CoRR
Haoya Li, Yuehaw Khoo, Yinuo Ren, Lexing Ying