Probabilistic Modeling

Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes NeurIPS 2020 Structural Causal Models Are (Solvable by) Credal Networks PGM 2020 Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models AISTATS 2020 Structured Probabilistic End-to-End Learning from Crowds IJCAI 2020 Strudel: Learning Structured-Decomposable Probabilistic Circuits PGM 2020 Submodel Decomposition for Solving Limited Memory Influence Diagrams (Student Abstract) AAAI 2020 Sum-Product Network Decompilation PGM 2020 Sum-Product Networks for Robust Automatic Speaker Identification Interspeech 2020 Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations PGM 2020 Switching Poisson Gamma Dynamical Systems IJCAI 2020 Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters NeurIPS 2020 Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes NeurIPS 2020 Temporal Logic Point Processes ICML 2020 Text-Based Ideal Points ACL 2020 The Autoencoding Variational Autoencoder NeurIPS 2020 The Boomerang Sampler ICML 2020 The continuous categorical: a novel simplex-valued exponential family ICML 2020 The Potts-Ising model for discrete multivariate data NeurIPS 2020 The Usual Suspects? Reassessing Blame for VAE Posterior Collapse ICML 2020 Topic Balancing with Additive Regularization of Topic Models ACL 2020 To Relieve Your Headache of Training an MRF, Take AdVIL ICLR 2020 Towards a Hierarchical Bayesian Model of Multi-View Anomaly Detection IJCAI 2020 Towards neural networks that provably know when they don't know ICLR 2020 Two Reformulation Approaches to Maximum-A-Posteriori Inference in Sum-Product Networks PGM 2020 Uncertain Natural Language Inference ACL 2020