Yian Ma

According to our database, Yian Ma authored at least 11 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo.

Xunpeng Huang, Difan Zou, Hanze Dong, Yian Ma, Tong Zhang

CoRR, 2024

2023

Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy.

Yingyu Lin, Yian Ma, Yu-Xiang Wang, Rachel Redberg

CoRR, 2023

Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?

Kyurae Kim, Yian Ma, Jacob R. Gardner

CoRR, 2023

Monte Carlo Sampling without Isoperimetry: A Reverse Diffusion Approach.

Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang

CoRR, 2023

Black-Box Variational Inference Converges.

Kyurae Kim, Kaiwen Wu, Jisu Oh, Yian Ma, Jacob R. Gardner

CoRR, 2023

Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation.

Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yian Ma

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Convergence of Black-Box Variational Inference.

Kyurae Kim, Jisu Oh, Kaiwen Wu, Yian Ma, Jacob R. Gardner

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Disentangled Multi-Fidelity Deep Bayesian Active Learning.

Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yian Ma, Rose Yu

Proceedings of the International Conference on Machine Learning, 2023

2021

DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting.

Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yian Ma, Rose Yu

CoRR, 2021

Variational refinement for importance sampling using the forward Kullback-Leibler divergence.

Ghassen Jerfel, Serena Lutong Wang, Clara Wong-Fannjiang, Katherine A. Heller, Yian Ma, Michael I. Jordan

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics.

Matthew D. Hoffman, Yian Ma

Proceedings of the 37th International Conference on Machine Learning, 2020