Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC for Large Neural Nets
Wu Lin*, Felix Dangel*, Runa Eschenhagen, Kirill Neklyudov, Agustinus Kristiadi, Richard Turner, Alireza Makhzani
ICML 2024
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arxiv]
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code]
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta, Pascal Poupart, Alán Aspuru-Guzik, Geoff Pleiss
ICML 2024
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arxiv]
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code]
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI
Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, Jose Miguel Hernandez Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
ICML 2024
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arxiv]
Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks
Ahmad Rashid, Serena Hacker, Guojun Zhang, Agustinus Kristiadi, Pascal Poupart
AISTATS 2024
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arxiv]
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code]
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
Agustinus Kristiadi, Felix Dangel, and Philipp Hennig
NeurIPS 2023
[Spotlight]
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arxiv]
Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
Agustinus Kristiadi, Runa Eschenhagen, and Philipp Hennig
NeurIPS 2022
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arxiv]
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code]
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks
Marius Hobbhahn, Agustinus Kristiadi, and Philipp Hennig
UAI 2022
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paper]
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code]
Being a Bit Frequentist Improves Bayesian Neural Networks
Agustinus Kristiadi, Matthias Hein, and Philipp Hennig
AISTATS 2022
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paper]
[
code]
Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference
Luca Rendsburg, Agustinus Kristiadi, Philipp Hennig, and Ulrike von Luxburg
AISTATS 2022
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paper]
[
code]
An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence
Agustinus Kristiadi, Matthias Hein, and Philipp Hennig
Laplace Redux -- Effortless Bayesian Deep Learning
Erik Daxberger*, Agustinus Kristiadi*, Alexander Immer*, Runa Eschenhagen*, Matthias Bauer, and Philipp Hennig
Learnable Uncertainty under Laplace Approximations
Agustinus Kristiadi, Matthias Hein, and Philipp Hennig
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks
Agustinus Kristiadi, Matthias Hein, and Philipp Hennig
Incorporating Literals into Knowledge Graph Embeddings
Agustinus Kristiadi*, Mohammad Asif Khan*, Denis Lukovnikov, Jens Lehmann, and Asja Fischer
Improving Response Selection in Multi-turn Dialogue Systems by Incorporating Domain Knowledge
Debanjan Chauduri, Agustinus Kristiadi, Jens Lehmann, Asja Fischer
Deep Convolutional Level Set Method for Image Segmentation
Agustinus Kristiadi and Pranowo
Journal of ICT Research and Applications 11.3 (2017)
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pdf]
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code]
Parallel Particle Swarm Optimization for Image Segmentation
Agustinus Kristiadi, Pranowo, and Paulus Mudjihartono