Probabilistic Modeling

Structure Learning Under Missing Data PGM 2018 Taming Performance Variability OSDI 2018 The Mean-Field Approximation: Information Inequalities, Algorithms, and Complexity COLT 2018 Turing: A Language for Flexible Probabilistic Inference AISTATS 2018 Uncertainty-aware generative models for inferring document class prevalence EMNLP 2018 Unifying DAGs and UGs PGM 2018 Unsupervised Image-to-Image Translation Using Domain-Specific Variational Information Bound NeurIPS 2018 Variational Bayesian Monte Carlo NeurIPS 2018 Variational Continual Learning ICLR 2018 Variational Fourier Features for Gaussian Processes JMLR 2018 Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition NeurIPS 2018 Variational Learning on Aggregate Outputs with Gaussian Processes NeurIPS 2018 Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task NeurIPS 2018 A Computational Model of Human Preferences for Pronoun Resolution EACL 2017 A Correlated Topic Model Using Word Embeddings IJCAI 2017 A Density-based Nonparametric Model for Online Event Discovery from the Social Media Data IJCAI 2017 A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering NeurIPS 2017 A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning NeurIPS 2017 A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models AISTATS 2017 A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics COLT 2017 A Lower Bound on the Partition Function of Attractive Graphical Models in the Continuous Case AISTATS 2017 A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings ACML 2017 An Infinite Hidden Markov Model With Similarity-Biased Transitions ICML 2017 A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks NeurIPS 2017 A Trust-based Mixture of Gaussian Processes Model for Reliable Regression in Participatory Sensing IJCAI 2017