Bayesian & Probabilistic

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 Generative Parser with a Discriminative Recognition Algorithm ACL 2017 Aggregating and Predicting Sequence Labels from Crowd Annotations ACL 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 Empirical Bayes Approach to Optimizing Machine Learning Algorithms NeurIPS 2017 An Infinite Hidden Markov Model With Similarity-Biased Transitions ICML 2017 A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks NeurIPS 2017 A Probabilistic Generative Grammar for Semantic Parsing CoNLL 2017 A Trust-based Mixture of Gaussian Processes Model for Reliable Regression in Participatory Sensing IJCAI 2017 A Unifying Framework for Probabilistic Belief Revision IJCAI 2017 Averaged Collapsed Variational Bayes Inference JMLR 2017 Bayesian Boolean Matrix Factorisation ICML 2017 Bayesian Compression for Deep Learning NeurIPS 2017 Bayesian Dynamic Mode Decomposition IJCAI 2017 Bayesian Eigenobjects: A Unified Framework for 3D Robot Perception RSS 2017 Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes NeurIPS 2017 Bayesian inference on random simple graphs with power law degree distributions ICML 2017 Bayesian Interaction Primitives: A SLAM Approach to Human-Robot Interaction CoRL 2017 Bayesian Modeling of Lexical Resources for Low-Resource Settings ACL 2017 Bayesian Models of Data Streams with Hierarchical Power Priors ICML 2017 Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity (Extended Abstract) IJCAI 2017 Bayesian Optimization with Gradients NeurIPS 2017