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Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes.

R. Novak, L. Xiao, Y. Bahri, J. Lee, G. Yang, J. Hron, D. Abolafia, J. Pennington, and J. Sohl-Dickstein. ICLR (Poster), OpenReview.net, (2019)

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Aemilian Hron

Jeanette Hron

Günther Jirikowski

Gustav Jirikowski

Irina Hron-Öberg

Other publications of authors with the same name

Concrete Dropout.Y. Gal, J. Hron, and A. Kendall. NIPS, page 3581-3590. (2017)The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments.M. Zilka, R. Fogliato, J. Hron, B. Butcher, C. Ashurst, and A. Weller. FAccT, page 1553-1569. ACM, (2023)Orthogonal Estimation of Wasserstein Distances.M. Rowland, J. Hron, Y. Tang, K. Choromanski, T. Sarlós, and A. Weller. AISTATS, volume 89 of Proceedings of Machine Learning Research, page 186-195. PMLR, (2019)Beyond Use-Cases: A Participatory Approach to Envisioning Data Science in Law Enforcement.C. Kearney, J. Hron, H. Kosc, and M. Zilka. FAccT, page 1809-1826. ACM, (2024)On Component Interactions in Two-Stage Recommender Systems.J. Hron, K. Krauth, M. Jordan, and N. Kilbertus. NeurIPS, page 2744-2757. (2021)Neural Tangents: Fast and Easy Infinite Neural Networks in Python.R. Novak, L. Xiao, J. Hron, J. Lee, A. Alemi, J. Sohl-Dickstein, and S. Schoenholz. CoRR, (2019)Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes.R. Novak, L. Xiao, Y. Bahri, J. Lee, G. Yang, J. Hron, D. Abolafia, J. Pennington, and J. Sohl-Dickstein. ICLR (Poster), OpenReview.net, (2019)Gaussian Process Behaviour in Wide Deep Neural NetworksA. Matthews, M. Rowland, J. Hron, R. Turner, and Z. Ghahramani. (2018)cite arxiv:1804.11271Comment: This work substantially extends the work of Matthews et al. (2018) published at the International Conference on Learning Representations (ICLR) 2018.Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning.D. Janz, J. Hron, P. Mazur, K. Hofmann, J. Hernández-Lobato, and S. Tschiatschek. NeurIPS, page 4509-4518. (2019)Infinite attention: NNGP and NTK for deep attention networks.J. Hron, Y. Bahri, J. Sohl-Dickstein, and R. Novak. ICML, volume 119 of Proceedings of Machine Learning Research, page 4376-4386. PMLR, (2020)

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Disambiguation of "Hron, Jiri"

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Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes.

Please choose a person to relate this publication to

Aemilian Hron

Jeanette Hron

Günther Jirikowski

Gustav Jirikowski

Irina Hron-Öberg

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Hron, Jiri"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes.

Please choose a person to relate this publication to

Aemilian Hron

Jeanette Hron

Günther Jirikowski

Gustav Jirikowski

Irina Hron-Öberg

Other publications of authors with the same name

Disambiguation

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history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes.