Alexander A. Alemi | DeepAI

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∙ 11/18/2022

Weighted Ensemble Self-Supervised Learning

Ensembling has proven to be a powerful technique for boosting model perf...

0 Yangjun Ruan, et al. ∙

∙ 02/15/2022

Bayesian Imitation Learning for End-to-End Mobile Manipulation

In this work we investigate and demonstrate benefits of a Bayesian appro...

11 Yuqing Du, et al. ∙

∙ 07/12/2021

A Closer Look at the Adversarial Robustness of Information Bottleneck Models

We study the adversarial robustness of information bottleneck models for...

0 Iryna Korshunova, et al. ∙

∙ 06/10/2021

Does Knowledge Distillation Really Work?

Knowledge distillation is a popular technique for training a small stude...

0 Samuel Stanton, et al. ∙

∙ 11/17/2020

VIB is Half Bayes

In discriminative settings such as regression and classification there a...

0 Alexander A. Alemi, et al. ∙

∙ 10/19/2020

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

While the decision-theoretic optimality of the Bayesian formalism under ...

0 Warren R. Morningstar, et al. ∙

∙ 06/16/2020

Density of States Estimation for Out-of-Distribution Detection

Perhaps surprisingly, recent studies have shown probabilistic model like...

0 Warren R. Morningstar, et al. ∙

∙ 02/13/2020

CEB Improves Model Robustness

We demonstrate that the Conditional Entropy Bottleneck (CEB) can improve...

0 Ian Fischer, et al. ∙

∙ 12/05/2019

Neural Tangents: Fast and Easy Infinite Neural Networks in Python

Neural Tangents is a library designed to enable research into infinite-w...

14 Roman Novak, et al. ∙

∙ 11/20/2019

Information in Infinite Ensembles of Infinitely-Wide Neural Networks

In this preliminary work, we study the generalization properties of infi...

0 Ravid Schwartz-Ziv, et al. ∙

∙ 10/23/2019

Variational Predictive Information Bottleneck

In classic papers, Zellner demonstrated that Bayesian inference could be...

0 Alexander A. Alemi, et al. ∙

∙ 10/21/2019

On Predictive Information Sub-optimality of RNNs

Certain biological neurons demonstrate a remarkable capability to optima...

0 Zhe Dong, et al. ∙

∙ 05/16/2019

On Variational Bounds of Mutual Information

Estimating and optimizing Mutual Information (MI) is core to many proble...

8 Ben Poole, et al. ∙

∙ 04/30/2019

On the Use of ArXiv as a Dataset

The arXiv has collected 1.5 million pre-print articles over 28 years, ho...

0 Colin B. Clement, et al. ∙

∙ 12/06/2018

β-VAEs can retain label information even at high compression

In this paper, we investigate the degree to which the encoding of a β-VA...

0 Emily Fertig, et al. ∙

∙ 07/11/2018

TherML: Thermodynamics of Machine Learning

In this work we offer a framework for reasoning about a wide class of ex...

2 Alexander A. Alemi, et al. ∙

∙ 07/02/2018

Uncertainty in the Variational Information Bottleneck

We present a simple case study, demonstrating that Variational Informati...

2 Alexander A. Alemi, et al. ∙

∙ 02/13/2018

GILBO: One Metric to Measure Them All

We propose a simple, tractable lower bound on the mutual information con...

0 Alexander A. Alemi, et al. ∙

∙ 11/01/2017

An Information-Theoretic Analysis of Deep Latent-Variable Models

We present an information-theoretic framework for understanding trade-of...

0 Alexander A. Alemi, et al. ∙

∙ 05/25/2017

Jeffrey's prior sampling of deep sigmoidal networks

Neural networks have been shown to have a remarkable ability to uncover ...

0 Lorien X. Hayden, et al. ∙

∙ 05/25/2015

Clustering via Content-Augmented Stochastic Blockmodels

Much of the data being created on the web contains interactions between ...

0 J. Massey Cashore, et al. ∙

∙ 03/18/2015

Text Segmentation based on Semantic Word Embeddings

We explore the use of semantic word embeddings in text segmentation algo...

0 Alexander A. Alemi, et al. ∙