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How Good is the Bayes Posterior in Deep Neural Networks Really?

F. Wenzel, K. Roth, B. Veeling, J. Swiatkowski, L. Tran, S. Mandt, J. Snoek, T. Salimans, R. Jenatton, and S. Nowozin. ICML, volume 119 of Proceedings of Machine Learning Research, page 10248-10259. PMLR, (2020)

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Michael Snoek

Heinrich Snoek

Horst-Peter Snoek

Erich Snoek

Gerd Snoek

Other publications of authors with the same name

Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks.S. Padhy, Z. Nado, J. Ren, J. Liu, J. Snoek, and B. Lakshminarayanan. CoRR, (2020)Combining Ensembles and Data Augmentation can Harm your Calibration.Y. Wen, G. Jerfel, R. Muller, M. Dusenberry, J. Snoek, B. Lakshminarayanan, and D. Tran. CoRR, (2020)Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning.Z. Nado, N. Band, M. Collier, J. Djolonga, M. Dusenberry, S. Farquhar, A. Filos, M. Havasi, R. Jenatton, G. Jerfel and 14 other author(s). CoRR, (2021)Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach.S. Ariafar, J. Gilmer, Z. Nado, J. Snoek, R. Jenatton, and G. Dahl. CoRR, (2021)Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure.S. Kim, P. Lu, C. Loh, J. Smith, J. Snoek, and M. Soljacic. Trans. Mach. Learn. Res., (2022)Sparse MoEs meet Efficient Ensembles.J. Allingham, F. Wenzel, Z. Mariet, B. Mustafa, J. Puigcerver, N. Houlsby, G. Jerfel, V. Fortuin, B. Lakshminarayanan, J. Snoek and 3 other author(s). Trans. Mach. Learn. Res., (2022)Nonparametric guidance of autoencoder representations using label information.J. Snoek, R. Adams, and H. Larochelle. J. Mach. Learn. Res., (2012)On Nonparametric Guidance for Learning Autoencoder Representations.J. Snoek, R. Adams, and H. Larochelle. AISTATS, volume 22 of JMLR Proceedings, page 1073-1080. JMLR.org, (2012)Learning Latent Permutations with Gumbel-Sinkhorn Networks.G. Mena, D. Belanger, S. Linderman, and J. Snoek. ICLR (Poster), OpenReview.net, (2018)The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks.J. Swiatkowski, K. Roth, B. Veeling, L. Tran, J. Dillon, J. Snoek, S. Mandt, T. Salimans, R. Jenatton, and S. Nowozin. ICML, volume 119 of Proceedings of Machine Learning Research, page 9289-9299. PMLR, (2020)

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Disambiguation of "Snoek, Jasper"

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How Good is the Bayes Posterior in Deep Neural Networks Really?

Please choose a person to relate this publication to

Michael Snoek

Heinrich Snoek

Horst-Peter Snoek

Erich Snoek

Gerd Snoek

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Snoek, Jasper"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML How Good is the Bayes Posterior in Deep Neural Networks Really?

Please choose a person to relate this publication to

Michael Snoek

Heinrich Snoek

Horst-Peter Snoek

Erich Snoek

Gerd Snoek

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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How Good is the Bayes Posterior in Deep Neural Networks Really?