Bayesian & Probabilistic

Bayesian Optimization using Pseudo-Points IJCAI 2020 Bayesian Pseudocoresets NeurIPS 2020 Bayesian Sparsification of Deep C-valued Networks ICML 2020 BayesSuites: An Open Web Framework for Visualization of Massive Bayesian Networks PGM 2020 BCTH: A Novel Text Hashing Approach via Bayesian Clustering AACL 2020 Bean Machine: A Declarative Probabilistic Programming Language For Efficient Programmable Inference PGM 2020 Belief Merging Operators as Maximum Likelihood Estimators IJCAI 2020 Beyond the Grounding Bottleneck: Datalog Techniques for Inference in Probabilistic Logic Programs AAAI 2020 Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties NeurIPS 2020 Bootstrapping neural processes NeurIPS 2020 BOSS: Bayesian Optimization over String Spaces NeurIPS 2020 BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic AAAI 2020 Building Causal Interaction Models by Recursive Unfolding PGM 2020 Capsule Routing via Variational Bayes AAAI 2020 CCA-Flow: Deep Multi-view Subspace Learning with Inverse Autoregressive Flow ACML 2020 Censored Quantile Regression Forest AISTATS 2020 Community-Based Group Graphical Lasso JMLR 2020 Complex-Valued Variational Autoencoder: A Novel Deep Generative Model for Direct Representation of Complex Spectra Interspeech 2020 Compositional uncertainty in deep Gaussian processes UAI 2020 Conditional Gaussian Distribution Learning for Open Set Recognition CVPR 2020 Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures PGM 2020 Conditioning and Processing: Techniques to Improve Information-Theoretic Generalization Bounds NeurIPS 2020 Conjugate Gradients for Kernel Machines JMLR 2020 Constraining Variational Inference with Geometric Jensen-Shannon Divergence NeurIPS 2020 Constructing a Chain Event Graph from a Staged Tree PGM 2020