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Sanyam Kapoor

Large Language Models Must Be Taught to Know What They Don't Know

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Jun 12, 2024
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Function-Space Regularization in Neural Networks: A Probabilistic Perspective

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Dec 28, 2023
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Should We Learn Most Likely Functions or Parameters?

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Nov 27, 2023
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PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization

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Nov 24, 2022
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Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors

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May 20, 2022
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On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification

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Mar 30, 2022
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When are Iterative Gaussian Processes Reliably Accurate?

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Dec 31, 2021
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A Simple and Fast Baseline for Tuning Large XGBoost Models

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Nov 12, 2021
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SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes

Jun 12, 2021
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Variational Auto-Regressive Gaussian Processes for Continual Learning

Jun 09, 2020
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