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07/27/2023
Speed Limits for Deep Learning
State-of-the-art neural networks require extreme computational power to ...
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07/14/2023
Variational Prediction
Bayesian inference offers benefits over maximum likelihood, but it also ...
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11/18/2022
Weighted Ensemble Self-Supervised Learning
Ensembling has proven to be a powerful technique for boosting model perf...
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02/15/2022
Bayesian Imitation Learning for End-to-End Mobile Manipulation
In this work we investigate and demonstrate benefits of a Bayesian appro...
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07/12/2021
A Closer Look at the Adversarial Robustness of Information Bottleneck Models
We study the adversarial robustness of information bottleneck models for...
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06/10/2021
Does Knowledge Distillation Really Work?
Knowledge distillation is a popular technique for training a small stude...
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11/17/2020
VIB is Half Bayes
In discriminative settings such as regression and classification there a...
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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 ...
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06/16/2020
Density of States Estimation for Out-of-Distribution Detection
Perhaps surprisingly, recent studies have shown probabilistic model like...
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02/13/2020
CEB Improves Model Robustness
We demonstrate that the Conditional Entropy Bottleneck (CEB) can improve...
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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...
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11/20/2019
Information in Infinite Ensembles of Infinitely-Wide Neural Networks
In this preliminary work, we study the generalization properties of infi...
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10/23/2019
Variational Predictive Information Bottleneck
In classic papers, Zellner demonstrated that Bayesian inference could be...
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10/21/2019
On Predictive Information Sub-optimality of RNNs
Certain biological neurons demonstrate a remarkable capability to optima...
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05/16/2019
On Variational Bounds of Mutual Information
Estimating and optimizing Mutual Information (MI) is core to many proble...
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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...
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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...
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07/11/2018
TherML: Thermodynamics of Machine Learning
In this work we offer a framework for reasoning about a wide class of ex...
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07/02/2018
Uncertainty in the Variational Information Bottleneck
We present a simple case study, demonstrating that Variational Informati...
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02/13/2018
GILBO: One Metric to Measure Them All
We propose a simple, tractable lower bound on the mutual information con...
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11/01/2017
An Information-Theoretic Analysis of Deep Latent-Variable Models
We present an information-theoretic framework for understanding trade-of...
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05/25/2017
Jeffrey's prior sampling of deep sigmoidal networks
Neural networks have been shown to have a remarkable ability to uncover ...
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05/25/2015
Clustering via Content-Augmented Stochastic Blockmodels
Much of the data being created on the web contains interactions between ...
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03/18/2015