Bayesian & Probabilistic

Improved Variational Bayesian Phylogenetic Inference with Normalizing Flows NeurIPS 2020 Improving Local Identifiability in Probabilistic Box Embeddings NeurIPS 2020 Imputing typological values via phylogenetic inference EMNLP 2020 Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations AAAI 2020 Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020 Influenza Forecasting Framework based on Gaussian Processes ICML 2020 Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip AAAI 2020 Interactive Anomaly Detection in Mixed Tabular Data using Bayesian Networks PGM 2020 Interactive Learning with Proactive Cognition Enhancement for Crowd Workers AAAI 2020 Interpretable Deep Gaussian Processes with Moments AISTATS 2020 Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model EMNLP 2020 Investigating Matureness of Probabilistic Graphical Models for Dry-Bulk Shipping PGM 2020 Joints in Random Forests NeurIPS 2020 Kernel-based Approach for Learning Causal Graphs from Mixed Data PGM 2020 Knowledge Transfer for Learning Markov Equivalence Classes PGM 2020 Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs JMLR 2020 L1-GP: L1 Adaptive Control with Bayesian Learning L4DC 2020 Label Error Correction and Generation through Label Relationships AAAI 2020 Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings NeurIPS 2020 Latent Geographical Factors for Analyzing the Evolution of Dialects in Contact EMNLP 2020 Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification JMLR 2020 Layering-MCMC for Structure Learning in Bayesian Networks UAI 2020 Learning Agent Representations for Ice Hockey NeurIPS 2020 Learning Bayesian Networks with Cops and Robbers PGM 2020 Learning Big Gaussian Bayesian Networks: Partition, Estimation and Fusion JMLR 2020