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Agustinus Kristiadi

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

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Feb 06, 2024
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Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC for Large Neural Nets

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Dec 16, 2023
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Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks

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Nov 07, 2023
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On the Disconnect Between Theory and Practice of Overparametrized Neural Networks

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Sep 29, 2023
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Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization

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Apr 17, 2023
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The Geometry of Neural Nets' Parameter Spaces Under Reparametrization

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Feb 14, 2023
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Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks

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May 20, 2022
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Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference

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Mar 07, 2022
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Mixtures of Laplace Approximations for Improved Post-Hoc Uncertainty in Deep Learning

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Nov 05, 2021
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Laplace Redux -- Effortless Bayesian Deep Learning

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Jun 28, 2021
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