probabilistic modeling

Equiprobable mappings in weighted constraint grammars ACL 2019 Evidence-based Trustworthiness ACL 2019 Expressive power of tensor-network factorizations for probabilistic modeling NeurIPS 2019 Flexible Modeling of Diversity with Strongly Log-Concave Distributions NeurIPS 2019 Gaussian Process Models of Sound Change in Indo-Aryan Dialectology ACL 2019 Generalized Boltzmann Machine with Deep Neural Structure AISTATS 2019 Generalized Maximum Entropy Estimation JMLR 2019 Generic Inference in Latent Gaussian Process Models JMLR 2019 Identifiability of Generalized Hypergeometric Distribution (GHD) Directed Acyclic Graphical Models AISTATS 2019 Improving Customer Satisfaction in Bike Sharing Systems through Dynamic Repositioning IJCAI 2019 Interpretable Word Embeddings via Informative Priors EMNLP 2019 Invariant-Equivariant Representation Learning for Multi-Class Data ICML 2019 Learning Determinantal Point Processes by Corrective Negative Sampling AISTATS 2019 Learning Deterministic Weighted Automata with Queries and Counterexamples NeurIPS 2019 Learning Mixtures of Plackett-Luce Models from Structured Partial Orders NeurIPS 2019 Learning Models from Data with Measurement Error: Tackling Underreporting ICML 2019 Learning Vine Copula Models for Synthetic Data Generation AAAI 2019 Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption UAI 2019 Markov Properties of Discrete Determinantal Point Processes AISTATS 2019 Modelling Instance-Level Annotator Reliability for Natural Language Labelling Tasks NAACL 2019 MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction CoRL 2019 Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes NeurIPS 2019 Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data AAAI 2019 Neural Finite-State Transducers: Beyond Rational Relations NAACL 2019 On Constrained Open-World Probabilistic Databases IJCAI 2019