publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2024

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    Posterior Uncertainty Quantification in Neural Networks using Data Augmentation
    Luhuan Wu and Sinead A Williamson
    In International Conference on Artificial Intelligence and Statistics, 2024

2023

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    Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
    Luhuan Wu Wu, Brian Trippe, Christian Naesseth, and 2 more authors
    In Conference on Neural Information Processing Systems, 2023

2022

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    Variational Nearest Neighbor Gaussian Process
    Luhuan Wu, Geoff Pleiss, and John Cunningham
    In International Conference on Machine Learning, 2022

2021

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    Bias-free Scalable Gaussian Processes via Randomized Truncations
    Andres Potapczynski, Luhuan Wu, Dan Biderman, and 2 more authors
    In International Conference on Machine Learning, 2021
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    Hierarchical Inducing Point Gaussian Process for Inter-domian Observations
    Luhuan Wu, Andrew Miller, Lauren Anderson, and 3 more authors
    In International Conference on Artificial Intelligence and Statistics, 2021

2020

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    Inverse Articulated-body Dynamics from Video via Variational Sequential Monte Carlo
    Dan Biderman, Christian A Naesseth, Luhuan Wu, and 6 more authors
    In NeurIPS Workshop on Differentiable Vision, Graphics, and Physics in Machine Learning, 2020

2019

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    Smoothing Nonlinear Variational Objectives with Sequential Monte Carlo
    Antonio Moretti, Zizhao Wang, Luhuan Wu, and 1 more author
    In ICLR Workshop on Deep Generative Models for Highly Structured Data, 2019