Dang, Meihua

11 publications

CVPR 2025 Personalized Preference Fine-Tuning of Diffusion Models Meihua Dang, Anikait Singh, Linqi Zhou, Stefano Ermon, Jiaming Song

ICML 2025 Scaling Probabilistic Circuits via Monarch Matrices Honghua Zhang, Meihua Dang, Benjie Wang, Stefano Ermon, Nanyun Peng, Guy Van Den Broeck

CVPR 2024 Diffusion Model Alignment Using Direct Preference Optimization Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, Nikhil Naik

ICLR 2023 Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL Baiting Zhu, Meihua Dang, Aditya Grover

ICML 2023 Tractable Control for Autoregressive Language Generation Honghua Zhang, Meihua Dang, Nanyun Peng, Guy Van Den Broeck

NeurIPSW 2022 Pareto-Efficient Decision Agents for Offline Multi-Objective Reinforcement Learning Baiting Zhu, Meihua Dang, Aditya Grover

NeurIPSW 2022 Pareto-Efficient Decision Agents for Offline Multi-Objective Reinforcement Learning Baiting Zhu, Meihua Dang, Aditya Grover

NeurIPS 2022 Sparse Probabilistic Circuits via Pruning and Growing Meihua Dang, Anji Liu, Guy Van den Broeck

AAAI 2021 Group Fairness by Probabilistic Modeling with Latent Fair Decisions YooJung Choi, Meihua Dang, Guy Van den Broeck

AAAI 2021 Juice: A Julia Package for Logic and Probabilistic Circuits Meihua Dang, Pasha Khosravi, Yitao Liang, Antonio Vergari, Guy Van den Broeck

PGM 2020 Strudel: Learning Structured-Decomposable Probabilistic Circuits Meihua Dang, Antonio Vergari, Guy Broeck