Lin, Lizhen

11 publications

ICML 2025 A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models Shivam Kumar, Yun Yang, Lizhen Lin

MLJ 2025 Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang, David B. Dunson

ICLR 2025 Conditional Diffusion Models Are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation Rong Tang, Lizhen Lin, Yun Yang

NeurIPS 2025 Posterior Contraction for Sparse Neural Networks in Besov Spaces with Intrinsic Dimensionality Kyeongwon Lee, Lizhen Lin, Jaewoo Park, Seonghyun Jeong

TMLR 2024 A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks Forough Fazeli-Asl, Michael Minyi Zhang, Lizhen Lin

NeurIPSW 2024 Bayesian Nonparametric Learning Using the Maximum Mean Discrepancy Measure for Synthetic Data Generation Forough Fazeli-Asl, Michael Minyi Zhang, Lizhen Lin

JMLR 2023 A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin

NeurIPS 2018 Communication Efficient Parallel Algorithms for Optimization on Manifolds Bayan Saparbayeva, Michael Zhang, Lizhen Lin

NeurIPS 2017 On Clustering Network-Valued Data Soumendu Sundar Mukherjee, Purnamrita Sarkar, Lizhen Lin

JMLR 2017 Robust and Scalable Bayes via a Median of Subset Posterior Measures Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson

ICML 2014 Scalable and Robust Bayesian Inference via the Median Posterior Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David Dunson