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Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning.

A. Immer, M. Bauer, V. Fortuin, G. Rätsch, and M. Khan. ICML, volume 139 of Proceedings of Machine Learning Research, page 4563-4573. PMLR, (2021)

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Martin Immer

Verena Immer

Karl Immer

Lena Immer

Peter Immer

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Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion.A. Meterez, A. Joudaki, F. Orabona, A. Immer, G. Rätsch, and H. Daneshmand. CoRR, (2023)Laplace Redux - Effortless Bayesian Deep Learning.E. Daxberger, A. Kristiadi, A. Immer, R. Eschenhagen, M. Bauer, and P. Hennig. NeurIPS, page 20089-20103. (2021)Sub-Matrix Factorization for Real-Time Vote Prediction.A. Immer, V. Kristof, M. Grossglauser, and P. Thiran. KDD, page 2280-2290. ACM, (2020)On the Identifiability and Estimation of Causal Location-Scale Noise Models.A. Immer, C. Schultheiss, J. Vogt, B. Schölkopf, P. Bühlmann, and A. Marx. CoRR, (2022)Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks.A. Möllers, A. Immer, E. Isufi, and V. Fortuin. CoRR, (2023)Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI.T. Papamarkou, M. Skoularidou, K. Palla, L. Aitchison, J. Arbel, D. Dunson, M. Filippone, V. Fortuin, P. Hennig, J. Hernández-Lobato and 15 other author(s). CoRR, (2024)Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels.A. Immer, T. van der Ouderaa, M. van der Wilk, G. Rätsch, and B. Schölkopf. ICML, volume 202 of Proceedings of Machine Learning Research, page 14333-14352. PMLR, (2023)Improving predictions of Bayesian neural nets via local linearization.A. Immer, M. Korzepa, and M. Bauer. AISTATS, volume 130 of Proceedings of Machine Learning Research, page 703-711. PMLR, (2021)Approximate Inference Turns Deep Networks into Gaussian Processes.M. Khan, A. Immer, E. Abedi, and M. Korzepa. NeurIPS, page 3088-3098. (2019)Continual Deep Learning by Functional Regularisation of Memorable Past.P. Pan, S. Swaroop, A. Immer, R. Eschenhagen, R. Turner, and M. Khan. NeurIPS, (2020)

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Disambiguation of "Immer, Alexander"

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Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning.

Please choose a person to relate this publication to

Martin Immer

Verena Immer

Karl Immer

Lena Immer

Peter Immer

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Immer, Alexander"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning.

Please choose a person to relate this publication to

Martin Immer

Verena Immer

Karl Immer

Lena Immer

Peter Immer

Other publications of authors with the same name

Disambiguation

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URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning.