bayesian model selection

A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints ICML 2025 Continuous Bayesian Model Selection for Multivariate Causal Discovery ICML 2025 Bivariate Causal Discovery using Bayesian Model Selection ICML 2024 Evidence Estimation in Gaussian Graphical Models Using a Telescoping Block Decomposition of the Precision Matrix JMLR 2024 Bayesian Data Selection JMLR 2023 Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels ICML 2023 Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations NeurIPS 2022 Last Layer Marginal Likelihood for Invariance Learning AISTATS 2022 Joint Inference for Neural Network Depth and Dropout Regularization NeurIPS 2021 Bayesian Model Selection with Graph Structured Sparsity JMLR 2020 Bayesian Model Selection Approach to Boundary Detection with Non-Local Priors NeurIPS 2018 Bayesian Model Selection for Change Point Detection and Clustering ICML 2018 Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach AISTATS 2018 Finding Galaxies in the Shadows of Quasars with Gaussian Processes ICML 2015 Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood ICML 2015 A recursive estimate for the predictive likelihood in a topic model AISTATS 2013 Factorized Asymptotic Bayesian Inference for Latent Feature Models NeurIPS 2013 Latent Data Association: Bayesian Model Selection for Multi-target Tracking ICCV 2013 Deterministic Bayesian inference for the $p*$ model AISTATS 2010 Probabilistic latent variable models for distinguishing between cause and effect NeurIPS 2010 Simple Exponential Family PCA AISTATS 2010 Automatic PCA Dimension Selection for High Dimensional Data and Small Sample Sizes JMLR 2008 Catching Up Faster in Bayesian Model Selection and Model Averaging NeurIPS 2007 On Sparsity and Overcompleteness in Image Models NeurIPS 2007 Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization NeurIPS 2006