Artículos con órdenes de acceso público - Agustinus KristiadiMás información
Disponibles en algún lugar: 12
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Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks
A Kristiadi, M Hein, P Hennig
ICML 2020, 2020
Órdenes: German Research Foundation, European Commission, Federal Ministry of …
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Laplace Redux--Effortless Bayesian Deep Learning
E Daxberger*, A Kristiadi*, A Immer*, R Eschenhagen*, M Bauer, ...
NeurIPS 2021, 2021
Órdenes: German Research Foundation, UK Engineering and Physical Sciences Research …
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Learnable Uncertainty under Laplace Approximations
A Kristiadi, M Hein, P Hennig
UAI 2021, 2021
Órdenes: German Research Foundation, European Commission, Federal Ministry of …
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Fast predictive uncertainty for classification with Bayesian deep networks
M Hobbhahn, A Kristiadi, P Hennig
UAI 2022, 2022
Órdenes: German Research Foundation, European Commission, Federal Ministry of …
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Predictive uncertainty quantification with compound density networks
A Kristiadi, S Däubener, A Fischer
Bayesian Deep Learning Workshop, NeurIPS 2019, 2019
Órdenes: German Research Foundation
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An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence
A Kristiadi, M Hein, P Hennig
NeurIPS 2021, 2021
Órdenes: German Research Foundation, European Commission, Federal Ministry of …
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Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
T Papamarkou, M Skoularidou, K Palla, L Aitchison, J Arbel, D Dunson, ...
ICML 2024, 2024
Órdenes: UK Engineering and Physical Sciences Research Council, Agence Nationale de …
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Being a Bit Frequentist Improves Bayesian Neural Networks
A Kristiadi, M Hein, P Hennig
AISTATS 2022, 2022
Órdenes: German Research Foundation, European Commission, Federal Ministry of …
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Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
A Kristiadi, R Eschenhagen, P Hennig
NeurIPS 2022, 2022
Órdenes: German Research Foundation, European Commission, Federal Ministry of …
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The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
A Kristiadi, F Dangel, P Hennig
NeurIPS 2023, 2023
Órdenes: European Commission
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Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference
L Rendsburg, A Kristiadi, P Hennig, U von Luxburg
AISTATS 2022, 2022
Órdenes: German Research Foundation, Federal Ministry of Education and Research, Germany
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Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC for Large Neural Nets
W Lin, F Dangel, R Eschenhagen, K Neklyudov, A Kristiadi, RE Turner, ...
ICML 2024, 2024
Órdenes: UK Engineering and Physical Sciences Research Council
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