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Bayesian Learning

455 directly classified papers

Papers per year

Papers

Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers NIPS 2024
A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression JMLR 2024
Making Better Use of Unlabelled Data in Bayesian Active Learning AISTATS 2024
MAPTree: Beating “Optimal” Decision Trees with Bayesian Decision Trees AAAI 2024
Full Bayesian Significance Testing for Neural Networks AAAI 2024
Sparse Variational Student-t Processes AAAI 2024
Beyond Single Stationary Policies: Meta-Task Players as Naturally Superior Collaborators NIPS 2024
Towards Modeling Uncertainties of Self-Explaining Neural Networks via Conformal Prediction AAAI 2024
Multi-Objective Bayesian Optimization with Active Preference Learning AAAI 2024
Constrained Bayesian Optimization under Partial Observations: Balanced Improvements and Provable Convergence AAAI 2024
Generalized Variational Inference via Optimal Transport AAAI 2024
Meta-Inverse Reinforcement Learning for Mean Field Games via Probabilistic Context Variables AAAI 2024
Dynamic Knowledge Injection for AIXI Agents AAAI 2024
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models AAAI 2024
HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems NIPS 2024
Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior AAAI 2024
Efficiently Acquiring Human Feedback with Bayesian Deep Learning EACL 2024
Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data AAAI 2024
Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs AAAI 2024
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification CVPR 2024
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood NIPS 2024
Solving Spectrum Unmixing as a Multi-Task Bayesian Inverse Problem with Latent Factors for Endmember Variability AAAI 2024
Bayes-optimal learning of an extensive-width neural network from quadratically many samples NIPS 2024
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach AISTATS 2023
Prediction-Oriented Bayesian Active Learning AISTATS 2023