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Erik Daxberger
Erik Daxberger
PhD at University of Cambridge & MPI for Intelligent Systems
Verified email at cam.ac.uk - Homepage
Title
Cited by
Cited by
Year
Embedding Models for Episodic Knowledge Graphs
Y Ma, V Tresp, EA Daxberger
Journal of Web Semantics, 2018
582018
Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining
A Tripp*, E Daxberger*, JM Hernández-Lobato
NeurIPS 2020, 2020
472020
Distributed Batch Gaussian Process Optimization
EA Daxberger, BKH Low
ICML 2017, 2017
412017
Laplace Redux--Effortless Bayesian Deep Learning
E Daxberger*, A Kristiadi*, A Immer*, R Eschenhagen*, M Bauer, ...
NeurIPS 2021, 2021
372021
Bayesian Deep Learning via Subnetwork Inference
E Daxberger, E Nalisnick, JU Allingham, J Antorán, ...
ICML 2021, 2021
33*2021
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection
E Daxberger, JM Hernández-Lobato
Bayesian Deep Learning Workshop, NeurIPS 2019, 2019
272019
Mixed-Variable Bayesian Optimization
E Daxberger*, A Makarova*, M Turchetta, A Krause
IJCAI 2020, 2020
252020
Mixtures of Laplace Approximations for Improved Post-Hoc Uncertainty in Deep Learning
R Eschenhagen, E Daxberger, P Hennig, A Kristiadi
Bayesian Deep Learning Workshop, NeurIPS 2021, 2021
62021
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning
J Antorán, D Janz, JU Allingham, E Daxberger, R Barbano, E Nalisnick, ...
ICML 2022, 2022
1*2022
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Articles 1–9