Bayesian Learning

Random Effect Bandits AISTATS 2022 Recursive autonomy identification-based learning of augmented naive Bayes classifiers PGM 2022 Scalable Bayesian Network Structure Learning with Splines PGM 2022 Scalable Gaussian-process regression and variable selection using Vecchia approximations JMLR 2022 Sparse Additive Gaussian Process Regression JMLR 2022 The Dual PC Algorithm for Structure Learning PGM 2022 Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets PGM 2022 Weakly Supervised Word Segmentation for Computational Language Documentation ACL 2022 Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling ICML 2022 Addressing Catastrophic Forgetting in Few-Shot Problems ICML 2021 A General Class of Transfer Learning Regression without Implementation Cost AAAI 2021 Bayesian Nonparametric Space Partitions: A Survey IJCAI 2021 BORE: Bayesian Optimization by Density-Ratio Estimation ICML 2021 Cautious Bayesian Optimization for Efficient and Scalable Policy Search L4DC 2021 Deep kernel processes ICML 2021 For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets NeurIPS 2021 GemBag: Group Estimation of Multiple Bayesian Graphical Models JMLR 2021 High Dimensional Level Set Estimation with Bayesian Neural Network AAAI 2021 Knowledge-Adaptation Priors NeurIPS 2021 Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system L4DC 2021 Learning Bayesian Networks from Ordinal Data JMLR 2021 Learning local modules in dynamic networks L4DC 2021 Near-Optimal Data Source Selection for Bayesian Learning L4DC 2021 Prediction by Anticipation: An Action-Conditional Prediction Method Based on Interaction Learning ICCV 2021 Probabilistic robust linear quadratic regulators with Gaussian processes L4DC 2021