Probabilistic Modeling

Statistical Model Criticism using Kernel Two Sample Tests NeurIPS 2015 Stochastic Expectation Propagation NeurIPS 2015 Submodular Point Processes with Applications to Machine learning AISTATS 2015 Swept Approximate Message Passing for Sparse Estimation ICML 2015 Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring NeurIPS 2015 The Human Kernel NeurIPS 2015 The Libra Toolkit for Probabilistic Models JMLR 2015 The Poisson Gamma Belief Network NeurIPS 2015 The Population Posterior and Bayesian Modeling on Streams NeurIPS 2015 Tractable Learning for Complex Probability Queries NeurIPS 2015 Transformation of Markov Random Fields for Marginal Distribution Estimation CVPR 2015 Unlocking neural population non-stationarities using hierarchical dynamics models NeurIPS 2015 Unsupervised Learning by Program Synthesis NeurIPS 2015 Variational Generative Stochastic Networks with Collaborative Shaping ICML 2015 Variational Inference for Gaussian Process Modulated Poisson Processes ICML 2015 Vector-Space Markov Random Fields via Exponential Families ICML 2015 Vector-Valued Property Elicitation COLT 2015 A Bayesian model for identifying hierarchically organised states in neural population activity NeurIPS 2014 Accelerating ABC methods using Gaussian processes AISTATS 2014 A Compilation Target for Probabilistic Programming Languages ICML 2014 A Deep and Tractable Density Estimator ICML 2014 Aerial Reconstructions via Probabilistic Data Fusion CVPR 2014 A Framework for Testing Identifiability of Bayesian Models of Perception NeurIPS 2014 Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy ICML 2014 A Junction Tree Framework for Undirected Graphical Model Selection JMLR 2014