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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Bayesian Prompt Learning for Image-Language Model Generalization ICCV 2023
No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities AISTATS 2023
Mixed-Effect Thompson Sampling AISTATS 2023
Noise-Aware Statistical Inference with Differentially Private Synthetic Data AISTATS 2023
Posterior Sampling for Deep Reinforcement Learning ICML 2023
Sparse Bayesian optimization AISTATS 2023
Bayesian online change point detection with Hilbert space approximate Student-t process ICML 2023
Plausible Uncertainties for Human Pose Regression ICCV 2023
Escaping The Curse of Dimensionality in Bayesian Model-Based Clustering JMLR 2023
Adversarial robustness of amortized Bayesian inference ICML 2023
On the Complexity of Bayesian Generalization ICML 2023
Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model AAAI 2023
Safety Verification of Nonlinear Systems with Bayesian Neural Network Controllers AAAI 2023
Robust and Adaptive Deep Learning via Bayesian Principles AAAI 2023
Bayesian Federated Learning: A Survey IJCAI 2023
Robust and Scalable Bayesian Online Changepoint Detection ICML 2023
Inferring Private Valuations from Behavioral Data in Bilateral Sequential Bargaining IJCAI 2023
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks ICML 2023
Learning-augmented count-min sketches via Bayesian nonparametrics JMLR 2023
It’s MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk EMNLP 2023
Overcoming Prior Misspecification in Online Learning to Rank AISTATS 2023
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference ICML 2023
Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group AISTATS 2023
Inverse-Reference Priors for Fisher Regularization of Bayesian Neural Networks AAAI 2023
Model-based Causal Discovery for Zero-Inflated Count Data JMLR 2023