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A Closer Look at the Adversarial Robustness of Information Bottleneck Models


Jul 12, 2021
Iryna Korshunova, David Stutz, Alexander A. Alemi, Olivia Wiles, Sven Gowal


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Does Knowledge Distillation Really Work?


Jun 10, 2021
Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson


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PAC$^m$-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime


Oct 19, 2020
Warren R. Morningstar, Alexander A. Alemi, Joshua V. Dillon

* Submitted to AISTATS 2021 

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Density of States Estimation for Out-of-Distribution Detection


Jun 22, 2020
Warren R. Morningstar, Cusuh Ham, Andrew G. Gallagher, Balaji Lakshminarayanan, Alexander A. Alemi, Joshua V. Dillon

* Submitted to NeurIPS. Corrected footnote from: "34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada" to "Preprint. Under review." 

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CEB Improves Model Robustness


Feb 13, 2020
Ian Fischer, Alexander A. Alemi


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Neural Tangents: Fast and Easy Infinite Neural Networks in Python


Dec 05, 2019
Roman Novak, Lechao Xiao, Jiri Hron, Jaehoon Lee, Alexander A. Alemi, Jascha Sohl-Dickstein, Samuel S. Schoenholz


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Information in Infinite Ensembles of Infinitely-Wide Neural Networks


Nov 23, 2019
Ravid Shwartz-Ziv, Alexander A. Alemi

* 2nd Symposium on Advances in Approximate Bayesian Inference, 2019 

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Variational Predictive Information Bottleneck


Oct 23, 2019
Alexander A. Alemi


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On Predictive Information Sub-optimality of RNNs


Oct 21, 2019
Zhe Dong, Deniz Oktay, Ben Poole, Alexander A. Alemi


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On Variational Bounds of Mutual Information


May 16, 2019
Ben Poole, Sherjil Ozair, Aaron van den Oord, Alexander A. Alemi, George Tucker

* ICML 2019 

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On the Use of ArXiv as a Dataset


Apr 30, 2019
Colin B. Clement, Matthew Bierbaum, Kevin P. O'Keeffe, Alexander A. Alemi

* 7 pages, 3 tables, 2 figures, ICLR 2019 workshop RLGM submission 

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$β$-VAEs can retain label information even at high compression


Dec 06, 2018
Emily Fertig, Aryan Arbabi, Alexander A. Alemi

* NeurIPS2018, BDL workshop 

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GILBO: One Metric to Measure Them All


Oct 27, 2018
Alexander A. Alemi, Ian Fischer

* Accepted at NIPS 2018 

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TherML: Thermodynamics of Machine Learning


Oct 04, 2018
Alexander A. Alemi, Ian Fischer

* Presented at the ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models 

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Uncertainty in the Variational Information Bottleneck


Jul 02, 2018
Alexander A. Alemi, Ian Fischer, Joshua V. Dillon

* 10 pages, 7 figures. Accepted to UAI 2018 - Uncertainty in Deep Learning Workshop 

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Fixing a Broken ELBO


Feb 13, 2018
Alexander A. Alemi, Ben Poole, Ian Fischer, Joshua V. Dillon, Rif A. Saurous, Kevin Murphy

* 21 pages, 9 figures 

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Deep Variational Information Bottleneck


Jul 17, 2017
Alexander A. Alemi, Ian Fischer, Joshua V. Dillon, Kevin Murphy

* 19 pages, 8 figures, Accepted to ICLR17 

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Jeffrey's prior sampling of deep sigmoidal networks


May 25, 2017
Lorien X. Hayden, Alexander A. Alemi, Paul H. Ginsparg, James P. Sethna


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Improved generator objectives for GANs


Dec 08, 2016
Ben Poole, Alexander A. Alemi, Jascha Sohl-Dickstein, Anelia Angelova

* NIPS 2016 Workshop on Adversarial Training 

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Clustering via Content-Augmented Stochastic Blockmodels


May 25, 2015
J. Massey Cashore, Xiaoting Zhao, Alexander A. Alemi, Yujia Liu, Peter I. Frazier


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