Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Variational Bayesian Optimal Experimental Design.

A. Foster, M. Jankowiak, E. Bingham, P. Horsfall, Y. Teh, T. Rainforth, and N. Goodman. NeurIPS, page 14036-14047. (2019)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Tom Ott University of Stuttgart

Tom Tenzer University of Stuttgart

Katharine Tomsich University of Stuttgart

Sandra Toms University of Stuttgart

Dr. phil. André Tomalka University of Stuttgart

Other publications of authors with the same name

A Statistical Approach to Assessing Neural Network Robustness.S. Webb, T. Rainforth, Y. Teh, and M. Kumar. CoRR, (2018)Nesting Probabilistic Programs.T. Rainforth. UAI, page 249-258. AUAI Press, (2018)Probabilistic structure discovery in time series data.D. Janz, B. Paige, T. Rainforth, J. van de Meent, and F. Wood. CoRR, (2016)LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models.Y. Zhou, B. Gram-Hansen, T. Kohn, T. Rainforth, H. Yang, and F. Wood. AISTATS, volume 89 of Proceedings of Machine Learning Research, page 148-157. PMLR, (2019)Bayesian Optimization for Probabilistic Programs.T. Rainforth, T. Le, J. van de Meent, M. Osborne, and F. Wood. NIPS, page 280-288. (2016)Variational Bayesian Optimal Experimental Design.A. Foster, M. Jankowiak, E. Bingham, P. Horsfall, Y. Teh, T. Rainforth, and N. Goodman. NeurIPS, page 14036-14047. (2019)Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support.Y. Zhou, H. Yang, Y. Teh, and T. Rainforth. CoRR, (2019)Disentangling Disentanglement.E. Mathieu, T. Rainforth, S. Narayanaswamy, and Y. Teh. CoRR, (2018)Faithful Inversion of Generative Models for Effective Amortized Inference.S. Webb, A. Golinski, R. Zinkov, S. Narayanaswamy, T. Rainforth, Y. Teh, and F. Wood. NeurIPS, page 3074-3084. (2018)Tighter Variational Bounds are Not Necessarily Better.T. Rainforth, A. Kosiorek, T. Le, C. Maddison, M. Igl, F. Wood, and Y. Teh. ICML, volume 80 of Proceedings of Machine Learning Research, page 4274-4282. PMLR, (2018)

PUMA

Disambiguation of "Rainforth, Tom"

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Variational Bayesian Optimal Experimental Design.

Please choose a person to relate this publication to

Tom Ott University of Stuttgart

Tom Tenzer University of Stuttgart

Katharine Tomsich University of Stuttgart

Sandra Toms University of Stuttgart

Dr. phil. André Tomalka University of Stuttgart

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Rainforth, Tom"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Variational Bayesian Optimal Experimental Design.

Please choose a person to relate this publication to

Tom Ott University of Stuttgart

Tom Tenzer University of Stuttgart

Katharine Tomsich University of Stuttgart

Sandra Toms University of Stuttgart

Dr. phil. André Tomalka University of Stuttgart

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Variational Bayesian Optimal Experimental Design.