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Luhuan Wu
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2020 – today
- 2024
- [c8]Luhuan Wu, Sinead A. Williamson:
Posterior Uncertainty Quantification in Neural Networks using Data Augmentation. AISTATS 2024: 3376-3384 - [i7]Luhuan Wu, Sinead Williamson:
Posterior Uncertainty Quantification in Neural Networks using Data Augmentation. CoRR abs/2403.12729 (2024) - 2023
- [c7]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 - [i6]Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham:
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models. CoRR abs/2306.17775 (2023) - 2022
- [c6]Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini:
Denoising Deep Generative Models. ICBINB 2022: 41-50 - [c5]Luhuan Wu, Geoff Pleiss, John P. Cunningham:
Variational nearest neighbor Gaussian process. ICML 2022: 24114-24130 - [i5]Luhuan Wu, Geoff Pleiss, John P. Cunningham:
Variational Nearest Neighbor Gaussian Processes. CoRR abs/2202.01694 (2022) - [i4]Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini:
Denoising Deep Generative Models. CoRR abs/2212.01265 (2022) - 2021
- [c4]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: 2926-2934 - [c3]Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham:
Bias-Free Scalable Gaussian Processes via Randomized Truncations. ICML 2021: 8609-8619 - [i3]Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham:
Bias-Free Scalable Gaussian Processes via Randomized Truncations. CoRR abs/2102.06695 (2021) - [i2]Luhuan Wu, Andrew Miller, Lauren Anderson
, Geoff Pleiss, David M. Blei, John P. Cunningham:
Hierarchical Inducing Point Gaussian Process for Inter-domain Observations. CoRR abs/2103.00393 (2021) - 2020
- [c2]Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu, Iddo Drori, Itsik Pe'er:
Variational Objectives for Markovian Dynamics with Backward Simulation. ECAI 2020: 1371-1378
2010 – 2019
- 2019
- [c1]Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu, Itsik Pe'er:
Smoothing Nonlinear Variational Objectives with Sequential Monte Carlo. DGS@ICLR 2019 - [i1]Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu, Iddo Drori, Itsik Pe'er:
Particle Smoothing Variational Objectives. CoRR abs/1909.09734 (2019)
Coauthor Index
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