Luhuan Wu

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 15

Top Topics

Gaussian Process

Diffusion Models

Top Venues

Publications

Luhuan Wu, Sinead Williamson
Posterior Uncertainty Quantification in Neural Networks using Data Augmentation. CoRR (2024)
Luhuan Wu, Sinead A. Williamson
Posterior Uncertainty Quantification in Neural Networks using Data Augmentation. AISTATS (2024)
Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models. CoRR (2023)
Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models. NeurIPS (2023)
Luhuan Wu, Geoff Pleiss, John P. Cunningham
Variational nearest neighbor Gaussian process. ICML (2022)
Luhuan Wu, Geoff Pleiss, John P. Cunningham
Variational Nearest Neighbor Gaussian Processes. CoRR (2022)
Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini
Denoising Deep Generative Models. CoRR (2022)
Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini
Denoising Deep Generative Models. ICBINB (2022)
Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss, David M. Blei, John P. Cunningham
Hierarchical Inducing Point Gaussian Process for Inter-domain Observations. CoRR (2021)
Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham
Bias-Free Scalable Gaussian Processes via Randomized Truncations. CoRR (2021)
Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss, David M. Blei, John P. Cunningham
Hierarchical Inducing Point Gaussian Process for Inter-domian Observations. AISTATS (2021)
Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham
Bias-Free Scalable Gaussian Processes via Randomized Truncations. ICML (2021)
Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu, Iddo Drori, Itsik Pe'er
Variational Objectives for Markovian Dynamics with Backward Simulation. ECAI (2020)
Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu, Itsik Pe'er
Smoothing Nonlinear Variational Objectives with Sequential Monte Carlo. DGS@ICLR (2019)
Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu, Iddo Drori, Itsik Pe'er
Particle Smoothing Variational Objectives. CoRR (2019)