Bayesian & Probabilistic

Student-t Process Regression with Student-t Likelihood IJCAI 2017 SVD-Based Screening for the Graphical Lasso IJCAI 2017 Targeting EEG/LFP Synchrony with Neural Nets NeurIPS 2017 Tensor Belief Propagation ICML 2017 The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities NeurIPS 2017 Tied Variational Autoencoder Backends for i-Vector Speaker Recognition Interspeech 2017 Tomography of the London Underground: a Scalable Model for Origin-Destination Data NeurIPS 2017 Tractability in Structured Probability Spaces NeurIPS 2017 VAE Learning via Stein Variational Gradient Descent NeurIPS 2017 Variational Autoencoded Regression: High Dimensional Regression of Visual Data on Complex Manifold CVPR 2017 Variational Bayesian Multiple Instance Learning With Gaussian Processes CVPR 2017 Variational Inference for Gaussian Process Models with Linear Complexity NeurIPS 2017 Variational Inference via χ Upper Bound Minimization NeurIPS 2017 Variational Policy for Guiding Point Processes ICML 2017 Weighted Model Integration with Orthogonal Transformations IJCAI 2017 XJNLP at SemEval-2017 Task 12: Clinical temporal information ex-traction with a Hybrid Model SemEval 2017 YASS: Yet Another Spike Sorter NeurIPS 2017 Zonotope Hit-and-run for Efficient Sampling from Projection DPPs ICML 2017 A Bayesian model for joint word alignment and part-of-speech transfer COLING 2016 A Bayesian Nonparametric Approach for Multi-label Classification ACML 2016 Acoustic-to-Articulatory Inversion Mapping Based on Latent Trajectory Gaussian Mixture Model Interspeech 2016 A Distribution-based Model to Learn Bilingual Word Embeddings COLING 2016 A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016 A General Framework for Constrained Bayesian Optimization using Information-based Search JMLR 2016 A Genetic Algorithm for Learning Parameters in Bayesian Networks using Expectation Maximization PGM 2016