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Bayesian Inference

4821 directly classified papers

Papers per year

Papers

Taming Continuous Posteriors for Latent Variational Dialogue Policies AAAI 2023
Phase-Informed Bayesian Ensemble Models Improve Performance of COVID-19 Forecasts AAAI 2023
An improved variational approximate posterior for the deep Wishart process UAI 2023
Graph classification Gaussian processes via spectral features UAI 2023
Bayesian numerical integration with neural networks UAI 2023
Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks AAAI 2023
Few-Shot Object Detection via Variational Feature Aggregation AAAI 2023
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods NIPS 2023
Multiply Robust Off-policy Evaluation and Learning under Truncation by Death ICML 2023
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation ICML 2023
Fairness-aware class imbalanced learning on multiple subgroups UAI 2023
Progressive Bayesian Inference for Scribble-Supervised Semantic Segmentation AAAI 2023
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice JMLR 2023
A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds JMLR 2023
Gibbsian Polar Slice Sampling ICML 2023
qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization AISTATS 2023
Fast Expectation Propagation for Heteroscedastic, Lasso-Penalized, and Quantile Regression JMLR 2023
Microcanonical Hamiltonian Monte Carlo JMLR 2023
Erratum: Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm JMLR 2023
The Bayesian Learning Rule JMLR 2023
Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information ICML 2023
Cosmic Microwave Background Recovery: A Graph-Based Bayesian Convolutional Network Approach AAAI 2023
Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance JMLR 2023
Unbiased Multilevel Monte Carlo Methods for Intractable Distributions: MLMC Meets MCMC JMLR 2023
A theory of representation learning gives a deep generalisation of kernel methods ICML 2023