Probabilistic Modeling

Cross-sectional Learning of Extremal Dependence among Financial Assets NeurIPS 2019 Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms NeurIPS 2019 Deep Bayesian Natural Language Processing ACL 2019 Deep Convolutional Networks as shallow Gaussian Processes ICLR 2019 Deep learning with differential Gaussian process flows AISTATS 2019 Dense Depth Posterior (DDP) From Single Image and Sparse Range CVPR 2019 Density Matching for Bilingual Word Embedding NAACL 2019 Detecting Overlapping and Correlated Communities without Pure Nodes: Identifiability and Algorithm ICML 2019 Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in Dialogue Generation EMNLP 2019 Dirichlet Simplex Nest and Geometric Inference ICML 2019 Discovering Context Effects from Raw Choice Data ICML 2019 Discovering Latent Covariance Structures for Multiple Time Series ICML 2019 Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography ICML 2019 Distribution calibration for regression ICML 2019 Domain-Size Aware Markov Logic Networks AISTATS 2019 DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures ICML 2019 Dynamically Personalized Detection of Hemorrhage MLHC 2019 Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems ICML 2019 Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables ICML 2019 Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model NeurIPS 2019 Eidos, INDRA, & Delphi: From Free Text to Executable Causal Models NAACL 2019 Embarrassingly Parallel Inference for Gaussian Processes JMLR 2019 EM-Fusion: Dynamic Object-Level SLAM With Probabilistic Data Association ICCV 2019 End-to-End Probabilistic Inference for Nonstationary Audio Analysis ICML 2019 Estimating Convergence of Markov chains with L-Lag Couplings NeurIPS 2019