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bayesian inference

1904 papers

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Also known as

MCMC MBR BI BVMM MAP

Co-occurring keywords

variational inference (2069) markov chain monte carlo (724) gaussian process (1198) probabilistic modeling (851) uncertainty quantification (1365) posterior distribution (259) bayesian learning (185) gibbs sampling (201) graphical model (863) probabilistic model (476)

Papers

Uncertainty informed optimal resource allocation with Gaussian process based Bayesian inference L4DC 2024
Probabilistic size-and-shape functional mixed models NIPS 2024
Diversification of Adaptive Policy for Effective Offline Reinforcement Learning IJCAI 2024
Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning IJCAI 2024
Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach WACV 2024
Bayesian Example Selection Improves In-Context Learning for Speech, Text and Visual Modalities EMNLP 2024
Quasi-Bayes meets Vines NIPS 2024
Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval NIPS 2023
Investigating a Generalization of Probabilistic Material Implication and Bayesian Conditionals UAI 2023
Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions ICML 2023
Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph JMLR 2023
The Bayesian Learning Rule JMLR 2023
Jana: Jointly amortized neural approximation of complex Bayesian models UAI 2023
Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance JMLR 2023
Divide-and-Conquer Fusion JMLR 2023
Estimating the Contamination Factor’s Distribution in Unsupervised Anomaly Detection ICML 2023
Posterior Consistency for Bayesian Relevance Vector Machines JMLR 2023
Approximate Post-Selective Inference for Regression with the Group LASSO JMLR 2023
Microcanonical Hamiltonian Monte Carlo JMLR 2023
A Bayesian Approach To Analysing Training Data Attribution In Deep Learning NIPS 2023
Optimistic Thompson Sampling-based algorithms for episodic reinforcement learning UAI 2023
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits ICML 2023
On the geometry of Stein variational gradient descent JMLR 2023
Learning Physical Models that Can Respect Conservation Laws ICML 2023
Uncertain Evidence in Probabilistic Models and Stochastic Simulators ICML 2023