
VIB is Half Bayes
In discriminative settings such as regression and classification there a...
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PAC^mBayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime
While the decisiontheoretic optimality of the Bayesian formalism under ...
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Density of States Estimation for OutofDistribution Detection
Perhaps surprisingly, recent studies have shown probabilistic model like...
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Automatic Differentiation Variational Inference with Mixtures
Automatic Differentiation Variational Inference (ADVI) is a useful tool ...
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The ktied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
Variational Bayesian Inference is a popular methodology for approximatin...
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tfp.mcmc: Modern Markov Chain Monte Carlo Tools Built for Modern Hardware
Markov chain Monte Carlo (MCMC) is widely regarded as one of the most im...
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Joint Distributions for TensorFlow Probability
A central tenet of probabilistic programming is that a model is specifie...
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Hydra: Preserving Ensemble Diversity for Model Distillation
Ensembles of models have been empirically shown to improve predictive pe...
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Likelihood Ratios for OutofDistribution Detection
Discriminative neural networks offer little or no performance guarantees...
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Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Modern machine learning methods including deep learning have achieved gr...
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NeuTralizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport
Hamiltonian Monte Carlo is a powerful algorithm for sampling from diffic...
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Uncertainty in the Variational Information Bottleneck
We present a simple case study, demonstrating that Variational Informati...
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TensorFlow Distributions
The TensorFlow Distributions library implements a vision of probability ...
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An InformationTheoretic Analysis of Deep LatentVariable Models
We present an informationtheoretic framework for understanding tradeof...
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Joshua V. Dillon
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