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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Robust and Adaptive Deep Learning via Bayesian Principles AAAI 2023
Adversarial robustness of amortized Bayesian inference ICML 2023
Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery AISTATS 2023
Learning Treatment Effects from Observational and Experimental Data AISTATS 2023
Surveillance Evasion Through Bayesian Reinforcement Learning AISTATS 2023
Minimax-Bayes Reinforcement Learning AISTATS 2023
Stochastic Tree Ensembles for Estimating Heterogeneous Effects AISTATS 2023
A Bayesian Bradley-Terry model to compare multiple ML algorithms on multiple data sets JMLR 2023
Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior AISTATS 2023
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits ICML 2023
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach AISTATS 2023
Model-based Causal Discovery for Zero-Inflated Count Data JMLR 2023
On the Complexity of Bayesian Generalization ICML 2023
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference ICML 2023
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks ICML 2023
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees JMLR 2023
An Eigenmodel for Dynamic Multilayer Networks JMLR 2023
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates ICML 2023
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge AISTATS 2023
Multilevel Bayesian Quadrature AISTATS 2023
Joint Word and Morpheme Segmentation with Bayesian Non-Parametric Models EACL 2023
Bayesian Hierarchical Models for Counterfactual Estimation AISTATS 2023
Disentangled Multi-Fidelity Deep Bayesian Active Learning ICML 2023
Sparse Spectral Bayesian Permanental Process with Generalized Kernel AISTATS 2023
Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture AISTATS 2023