Probabilistic Modeling

Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models NeurIPS 2017 Expectation Propagation for t-Exponential Family Using q-Algebra NeurIPS 2017 Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract) IJCAI 2017 Fast Sparse Gaussian Markov Random Fields Learning Based on Cholesky Factorization IJCAI 2017 Filtering Variational Objectives NeurIPS 2017 Flexible statistical inference for mechanistic models of neural dynamics NeurIPS 2017 Gauging Variational Inference NeurIPS 2017 Generalized Pólya Urn for Time-Varying Pitman-Yor Processes JMLR 2017 GibbsNet: Iterative Adversarial Inference for Deep Graphical Models NeurIPS 2017 GP CaKe: Effective brain connectivity with causal kernels NeurIPS 2017 Grammar Variational Autoencoder ICML 2017 Gray-box Inference for Structured Gaussian Process Models AISTATS 2017 Grounding Abstract Spatial Concepts for Language Interaction with Robots IJCAI 2017 GUIR at SemEval-2017 Task 12: A Framework for Cross-Domain Clinical Temporal Information Extraction SemEval 2017 Hierarchical Implicit Models and Likelihood-Free Variational Inference NeurIPS 2017 Hinge-Loss Markov Random Fields and Probabilistic Soft Logic JMLR 2017 Horde of Bandits using Gaussian Markov Random Fields AISTATS 2017 Improving Stochastic Block Models by Incorporating Power-Law Degree Characteristic IJCAI 2017 Improving Variational Methods via Pairwise Linear Response Identities JMLR 2017 Inference Compilation and Universal Probabilistic Programming AISTATS 2017 Inference in Graphical Models via Semidefinite Programming Hierarchies NeurIPS 2017 Inferring Generative Model Structure with Static Analysis NeurIPS 2017 Information Projection and Approximate Inference for Structured Sparse Variables AISTATS 2017 Inverse Filtering for Hidden Markov Models NeurIPS 2017 JU CSE NLP @ SemEval 2017 Task 7: Employing Rules to Detect and Interpret English Puns SemEval 2017