Bayesian & Probabilistic

Gray-box Inference for Structured Gaussian Process Models AISTATS 2017 GUIR at SemEval-2017 Task 12: A Framework for Cross-Domain Clinical Temporal Information Extraction SemEval 2017 Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery Interspeech 2017 Hierarchical Implicit Models and Likelihood-Free Variational Inference NeurIPS 2017 Hierarchical Methods of Moments NeurIPS 2017 High Dimensional Bayesian Optimization using Dropout IJCAI 2017 High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm ICML 2017 Hyperspherical Query Likelihood Models with Word Embeddings IJCNLP 2017 Identification of Gaussian Process State Space Models NeurIPS 2017 Improving Semantic Composition with Offset Inference ACL 2017 Improving the Expected Improvement Algorithm NeurIPS 2017 Improving Variational Methods via Pairwise Linear Response Identities JMLR 2017 Inferring Generative Model Structure with Static Analysis NeurIPS 2017 Integrating Specialized Classifiers Based on Continuous Time Markov Chain IJCAI 2017 Inverse Filtering for Hidden Markov Models NeurIPS 2017 LABDA at SemEval-2017 Task 10: Extracting Keyphrases from Scientific Publications by combining the BANNER tool and the UMLS Semantic Network SemEval 2017 Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks NeurIPS 2017 Latent Feature Lasso ICML 2017 Latent Variable Dialogue Models and their Diversity EACL 2017 Lean Crowdsourcing: Combining Humans and Machines in an Online System CVPR 2017 Learning Chordal Markov Networks via Branch and Bound NeurIPS 2017 Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo ICML 2017 Learning Determinantal Point Processes with Moments and Cycles ICML 2017 Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes NeurIPS 2017 Learning Hawkes Processes from Short Doubly-Censored Event Sequences ICML 2017