pac-bayesian theory

Epistemic Uncertainty and Excess Risk in Variational Inference AISTATS 2025 Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation JMLR 2025 Graph Neural Networks with a Distribution of Parametrized Graphs ICML 2024 Information-Theoretic Generalization Bounds for Transductive Learning and its Applications JMLR 2024 Meta-Learning via PAC-Bayesian with Data-Dependent Prior: Generalization Bounds from Local Entropy IJCAI 2024 Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks AISTATS 2024 Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets JMLR 2024 Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion AISTATS 2023 Optimization and Bayes: A Trade-off for Overparameterized Neural Networks NeurIPS 2023 PAC-Bayesian Generalization Bounds for Adversarial Generative Models ICML 2023 Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory NeurIPS 2023 Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective NeurIPS 2022 An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference JMLR 2022 Failure Prediction with Statistical Guarantees for Vision-Based Robot Control RSS 2022 Non-Vacuous Generalisation Bounds for Shallow Neural Networks ICML 2022 On PAC-Bayesian reconstruction guarantees for VAEs AISTATS 2022 PAC-Bayesian Bounds on Rate-Efficient Classifiers ICML 2022 A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks ICLR 2021 Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning NeurIPS 2021 Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes AISTATS 2021 Task-Driven Out-of-Distribution Detection with Statistical Guarantees for Robot Learning CoRL 2021 Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning AAAI 2020 Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis ICML 2020 PAC-Bayesian Bound for the Conditional Value at Risk NeurIPS 2020 PAC-Bayesian Contrastive Unsupervised Representation Learning UAI 2020