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David Dunson

Duke University

Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI

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Feb 06, 2024
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Spectral Gap Regularization of Neural Networks

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Apr 06, 2023
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Hierarchical shrinkage Gaussian processes: applications to computer code emulation and dynamical system recovery

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Feb 01, 2023
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Multiscale Graph Comparison via the Embedded Laplacian Distance

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Jan 28, 2022
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Gaussian Process Subspace Regression for Model Reduction

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Jul 09, 2021
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Statistical Guarantees for Transformation Based Models with Applications to Implicit Variational Inference

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Nov 04, 2020
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Principal Ellipsoid Analysis (PEA): Efficient non-linear dimension reduction & clustering

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Sep 07, 2020
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Bayesian neural networks and dimensionality reduction

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Aug 19, 2020
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Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity

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Apr 10, 2020
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Fiedler Regularization: Learning Neural Networks with Graph Sparsity

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Mar 02, 2020
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