The PAC-Bayes Guarantee

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NIPS 2016 spotlight - PAC Bayesian Theory Meets Bayesian Inference

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PAC-Bayesian approaches to understanding generalization in deep learning - Gintare Dziugaite

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An Introduction to PAC-Bayes

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[ML/DL] PAC-Bayesian Bound for Deep Learning Models

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Part 1: generalization and PAC bayesian learning

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Towards self-certified learning: Probabilistic neural networks trained by PAC-Bayes with Backprop

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AISTATS 2023: PAC-Bayesian Learning of Optimization Algorithms

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CS 159 (Spring 2021) -- PAC-Bayesian Theory

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François Laviolette - A Tutorial on PAC-Bayesian Theory (Talk)

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PAC-Bayesian Contrastive Unsupervised Representation Learning

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PAC Bayesian Learning and Domain Adaptation

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CVPR2023: Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization

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Studying Generalization in Deep Learning via PAC-Bayes

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MLSS 2021 Taipei- An intro to Statistical Learning Theory and PAC-Bayes Analysis (John Shawe-Taylor)

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A (condensed) primer on PAC-Bayesian Learning followed by News from the PAC-Bayes frontline

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PAC-Bayesian Contrastive Unsupervised Representation Learning

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PAC-Bayesian Machine Learning: Learning by Optimizing a Performance Guarantee

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A (condensed) primer on PAC-Bayesian Learning

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MAIS Poster 10: PAC Bayesian Binary Activated Deep Neural Networks

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