Probabilistic Modeling

Learning Tree Structures from Noisy Data AISTATS 2019 Leveraging Structural and Semantic Correspondence for Attribute-Oriented Aspect Sentiment Discovery EMNLP 2019 Lifted Hinge-Loss Markov Random Fields AAAI 2019 Lifted Message Passing for Hybrid Probabilistic Inference IJCAI 2019 Lifted Weight Learning of Markov Logic Networks Revisited AISTATS 2019 Marginal Inference in Continuous Markov Random Fields Using Mixtures AAAI 2019 Markov Properties of Discrete Determinantal Point Processes AISTATS 2019 Markov Random Fields for Collaborative Filtering NeurIPS 2019 Matched Bipartite Block Model with Covariates JMLR 2019 Maximum Likelihood for Gaussian Process Classification and Generalized Linear Mixed Models under Case-Control Sampling JMLR 2019 Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds ICLR 2019 Meimei: An Efficient Probabilistic Approach for Semantically Annotating Tables AAAI 2019 Meta-Learning Probabilistic Inference for Prediction ICLR 2019 Metropolis-Hastings Generative Adversarial Networks ICML 2019 Minimum Stein Discrepancy Estimators NeurIPS 2019 Model Comparison for Semantic Grouping ICML 2019 Modeling Behavioral Aspects of Social Media Discourse for Moral Classification NAACL 2019 Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes NeurIPS 2019 Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations NeurIPS 2019 Modeling Markedness with a Split-and-Merger Model of Sound Change ACL 2019 Modelling Instance-Level Annotator Reliability for Natural Language Labelling Tasks NAACL 2019 Modelling Uncertainty in Collaborative Document Quality Assessment EMNLP 2019 Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic ICLR 2019 Moment-Based Variational Inference for Markov Jump Processes ICML 2019 Multiple Futures Prediction NeurIPS 2019