Probabilistic Modeling

Hardness of Identity Testing for Restricted Boltzmann Machines and Potts models COLT 2020 Hawkesian Graphical Event Models PGM 2020 HCNAF: Hyper-Conditioned Neural Autoregressive Flow and its Application for Probabilistic Occupancy Map Forecasting CVPR 2020 Healing Products of Gaussian Process Experts ICML 2020 Hidden Markov Nonlinear ICA: Unsupervised Learning from Nonstationary Time Series UAI 2020 Hierarchical Multi-Grained Generative Model for Expressive Speech Synthesis Interspeech 2020 ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA NeurIPS 2020 Identifiability of Additive Noise Models Using Conditional Variances JMLR 2020 Identifying signal and noise structure in neural population activity with Gaussian process factor models NeurIPS 2020 Improved Model for Vocal Folds with a Polyp with Potential Application Interspeech 2020 Improving Local Identifiability in Probabilistic Box Embeddings NeurIPS 2020 Information Theoretic Optimal Learning of Gaussian Graphical Models COLT 2020 Inter-domain Deep Gaussian Processes ICML 2020 Investigating Matureness of Probabilistic Graphical Models for Dry-Bulk Shipping PGM 2020 Joints in Random Forests NeurIPS 2020 Kernel Conditional Density Operators AISTATS 2020 Knowing-How under Uncertainty (Extended Abstract) IJCAI 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 Variable Modelling with Hyperbolic Normalizing Flows ICML 2020 Layering-MCMC for Structure Learning in Bayesian Networks UAI 2020 Learning Big Gaussian Bayesian Networks: Partition, Estimation and Fusion JMLR 2020 Learning Constrained Dynamics with Gauss’ Principle adhering Gaussian Processes L4DC 2020 Learning decomposable models by coarsening PGM 2020 Learning General Latent-Variable Graphical Models with Predictive Belief Propagation AAAI 2020