Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement

13 July 2023

Kaixuan Huang

Mengdi Wang

Papers citing "Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement"

32 / 32 papers shown

Title
Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning Jifeng Hu Sili Huang Z. Yang Shengchao Hu Li Shen H. Chen Lichao Sun Yi-Ju Chang Dacheng Tao OffRL 143 0 0 03 May 2025
Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design Chenyu Wang Masatoshi Uehara Yichun He Amy Wang Tommaso Biancalani Avantika Lal Tommi Jaakkola Sergey Levine Hanchen Wang Aviv Regev 53 8 0 17 Oct 2024
Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow Fu-Yun Wang Ling Yang Zhaoyang Huang Mengdi Wang Hongsheng Li 31 13 0 09 Oct 2024
Geometric Representation Condition Improves Equivariant Molecule Generation Zian Li Cai Zhou Xiyuan Wang Xingang Peng Muhan Zhang 45 1 0 04 Oct 2024
Latent Diffusion Models for Controllable RNA Sequence Generation Kaixuan Huang Yukang Yang Kaidi Fu Yanyi Chu Le Cong Mengdi Wang 42 1 0 15 Sep 2024
Forward KL Regularized Preference Optimization for Aligning Diffusion Policies Zhao Shan Chenyou Fan Shuang Qiu Jiyuan Shi Chenjia Bai 33 4 0 09 Sep 2024
Constrained Diffusion Models via Dual Training Shervin Khalafi Dongsheng Ding Alejandro Ribeiro 40 3 0 27 Aug 2024
OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning Yi-Fan Yao Zhepeng Cen Wenhao Ding Hao-ming Lin Shiqi Liu Tingnan Zhang Wenhao Yu Ding Zhao OffRL OnRL 49 1 0 19 Jul 2024
Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review Masatoshi Uehara Yulai Zhao Tommaso Biancalani Sergey Levine 63 22 0 18 Jul 2024
Provable Statistical Rates for Consistency Diffusion Models Zehao Dou Minshuo Chen Mengdi Wang Zhuoran Yang DiffM 34 3 0 23 Jun 2024
Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models Masatoshi Uehara Yulai Zhao Ehsan Hajiramezanali Gabriele Scalia Gökçen Eraslan Avantika Lal Sergey Levine Tommaso Biancalani 47 13 0 30 May 2024
AI Risk Management Should Incorporate Both Safety and Security Xiangyu Qi Yangsibo Huang Yi Zeng Edoardo Debenedetti Jonas Geiping ... Chaowei Xiao Bo-wen Li Dawn Song Peter Henderson Prateek Mittal AAML 48 10 0 29 May 2024
U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models Song Mei 3DV AI4CE DiffM 41 11 0 29 Apr 2024
Gradient Guidance for Diffusion Models: An Optimization Perspective Yingqing Guo Hui Yuan Yukang Yang Minshuo Chen Mengdi Wang 27 20 0 23 Apr 2024
An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization Minshuo Chen Song Mei Jianqing Fan Mengdi Wang VLM MedIm DiffM 37 48 0 11 Apr 2024
Regularized Conditional Diffusion Model for Multi-Task Preference Alignment Xudong Yu Chenjia Bai Haoran He Changhong Wang Xuelong Li 34 6 0 07 Apr 2024
Diffusion Model for Data-Driven Black-Box Optimization Zihao Li Hui Yuan Kaixuan Huang Chengzhuo Ni Yinyu Ye Minshuo Chen Mengdi Wang DiffM 37 9 0 20 Mar 2024
Box It to Bind It: Unified Layout Control and Attribute Binding in T2I Diffusion Models Ashkan Taghipour Morteza Ghahremani Bennamoun Aref Miri Rekavandi Hamid Laga F. Boussaïd DiffM 32 5 0 27 Feb 2024
A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data Antonio Sclocchi Alessandro Favero M. Wyart DiffM 41 26 0 26 Feb 2024
Feedback Efficient Online Fine-Tuning of Diffusion Models Masatoshi Uehara Yulai Zhao Kevin Black Ehsan Hajiramezanali Gabriele Scalia N. Diamant Alex Tseng Sergey Levine Tommaso Biancalani 27 21 0 26 Feb 2024
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control Masatoshi Uehara Yulai Zhao Kevin Black Ehsan Hajiramezanali Gabriele Scalia N. Diamant Alex Tseng Tommaso Biancalani Sergey Levine 42 42 0 23 Feb 2024
From Function to Distribution Modeling: A PAC-Generative Approach to Offline Optimization Qiang Zhang Ruida Zhou Yang Shen Tie Liu OffRL 41 1 0 04 Jan 2024
Analysis of learning a flow-based generative model from limited sample complexity Hugo Cui Florent Krzakala Eric Vanden-Eijnden Lenka Zdeborová DRL 38 17 0 05 Oct 2023
Deep Networks as Denoising Algorithms: Sample-Efficient Learning of Diffusion Models in High-Dimensional Graphical Models Song Mei Yuchen Wu DiffM 28 26 0 20 Sep 2023
Diffusion Models are Minimax Optimal Distribution Estimators Kazusato Oko Shunta Akiyama Taiji Suzuki DiffM 72 85 0 03 Mar 2023
Convergence of score-based generative modeling for general data distributions Holden Lee Jianfeng Lu Yixin Tan DiffM 191 128 0 26 Sep 2022
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions Sitan Chen Sinho Chewi Jungshian Li Yuanzhi Li Adil Salim Anru R. Zhang DiffM 135 246 0 22 Sep 2022
Diffusion-LM Improves Controllable Text Generation Xiang Lisa Li John Thickstun Ishaan Gulrajani Percy Liang Tatsunori B. Hashimoto AI4CE 173 776 0 27 May 2022
Planning with Diffusion for Flexible Behavior Synthesis Michael Janner Yilun Du J. Tenenbaum Sergey Levine DiffM 202 627 0 20 May 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 313 11,915 0 04 Mar 2022
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 197 260 0 18 Apr 2021
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP Timo Schick Sahana Udupa Hinrich Schütze 259 374 0 28 Feb 2021