Bayesian Learning

Value-Distributional Model-Based Reinforcement Learning JMLR 2024 Variational Delayed Policy Optimization NeurIPS 2024 A Bayesian approach for bandit online optimization with switching cost UAI 2023 A Bayesian approach to breaking things: efficiently predicting and repairing failure modes via sampling CoRL 2023 A Bayesian Bradley-Terry model to compare multiple ML algorithms on multiple data sets JMLR 2023 Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference ICLR 2023 Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations NeurIPS 2023 AdaVAE: Bayesian Structural Adaptation for Variational Autoencoders NeurIPS 2023 Adversarial Bayesian Augmentation for Single-Source Domain Generalization ICCV 2023 Adversarial robustness of amortized Bayesian inference ICML 2023 A Finite-Particle Convergence Rate for Stein Variational Gradient Descent NeurIPS 2023 Aligning Language Models with Human Preferences via a Bayesian Approach NeurIPS 2023 An Eigenmodel for Dynamic Multilayer Networks JMLR 2023 An Empirical Bayes Framework for Open-Domain Dialogue Generation EMNLP 2023 A normative theory of social conflict NeurIPS 2023 Approximate Bayesian Inference with Stein Functional Variational Gradient Descent ICLR 2023 Approximate Thompson Sampling via Epistemic Neural Networks UAI 2023 Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture AISTATS 2023 Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression NeurIPS 2023 Autonomous Navigation, Mapping and Exploration with Gaussian Processes RSS 2023 Balancing Risk and Reward: A Batched-Bandit Strategy for Automated Phased Release NeurIPS 2023 Batch Bayesian Optimization For Replicable Experimental Design NeurIPS 2023 Bayesian Active Causal Discovery with Multi-Fidelity Experiments NeurIPS 2023 Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior AISTATS 2023 Bayesian Cross-Modal Alignment Learning for Few-Shot Out-of-Distribution Generalization AAAI 2023