Bayesian & Probabilistic

Batch Normalized Deep Boltzmann Machines ACML 2018 Bayesian Alignments of Warped Multi-Output Gaussian Processes NeurIPS 2018 Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments NeurIPS 2018 Bayesian Generalized Kernel Inference for Terrain Traversability Mapping CoRL 2018 Bayesian Model-Agnostic Meta-Learning NeurIPS 2018 Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data NeurIPS 2018 Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences AISTATS 2018 Bayesian Network Classifiers Under the Ensemble Perspective PGM 2018 Bayesian Network Structure Learning with Side Constraints PGM 2018 Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling AISTATS 2018 Bayesian Optimization of Combinatorial Structures ICML 2018 Bayesian RL for Goal-Only Rewards CoRL 2018 Bayesian Semi-supervised Learning with Graph Gaussian Processes NeurIPS 2018 Boosting Variational Inference: an Optimization Perspective AISTATS 2018 Bucket Renormalization for Approximate Inference ICML 2018 Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means AISTATS 2018 Cascading Sum-Product Networks using Robustness PGM 2018 Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models NeurIPS 2018 Causal Structure Learning via Temporal Markov Networks PGM 2018 Classifier Learning With Prior Probabilities for Facial Action Unit Recognition CVPR 2018 Clustering Induced Kernel Learning ACML 2018 Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data NeurIPS 2018 Compressing Neural Networks using the Variational Information Bottleneck ICML 2018 Computationally and statistically efficient learning of causal Bayes nets using path queries NeurIPS 2018 Conditional Noise-Contrastive Estimation of Unnormalised Models ICML 2018