Probabilistic Modeling

MRFMap: Online Probabilistic 3D Mapping using Forward Ray Sensor Models RSS 2020 Multi-Hypothesis Machine Translation Evaluation ACL 2020 Multiplicative Gaussian Particle Filter AISTATS 2020 Multi-Speaker Text-to-Speech Synthesis Using Deep Gaussian Processes Interspeech 2020 Multi-task Causal Learning with Gaussian Processes NeurIPS 2020 Neural Clustering Processes ICML 2020 NGBoost: Natural Gradient Boosting for Probabilistic Prediction ICML 2020 Non-Parametric Calibration for Classification AISTATS 2020 Nonparametric graphical model for counts JMLR 2020 Non-reversible Gaussian processes for identifying latent dynamical structure in neural data NeurIPS 2020 Non-separable Non-stationary random fields ICML 2020 Normalizing Kalman Filters for Multivariate Time Series Analysis NeurIPS 2020 On a possibility of gradual model-learning PGM 2020 On the (In)tractability of Computing Normalizing Constants for the Product of Determinantal Point Processes ICML 2020 On the Relationship Between Probabilistic Circuits and Determinantal Point Processes UAI 2020 Ordering Variables for Weighted Model Integration UAI 2020 Parallels Between Phase Transitions and Circuit Complexity? COLT 2020 Particle Filter Recurrent Neural Networks AAAI 2020 Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes AISTATS 2020 PCMC-Net: Feature-based Pairwise Choice Markov Chains ICLR 2020 PGM_PyLib: A Toolkit for Probabilistic Graphical Models in Python PGM 2020 PIDS: An Intelligent Electric Power Management Platform AAAI 2020 PoRB-Nets: Poisson Process Radial Basis Function Networks UAI 2020 Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts NeurIPS 2020 Predictive Uncertainty Estimation for Tractable Deep Probabilistic Models IJCAI 2020