Bayesian & Probabilistic

Variational Fourier Features for Gaussian Processes JMLR 2018 Variational Inference and Deep Generative Models ACL 2018 Variational Inference based on Robust Divergences AISTATS 2018 Variational Inference with Tail-adaptive f-Divergence NeurIPS 2018 Variational Knowledge Graph Reasoning NAACL 2018 Variational Learning on Aggregate Outputs with Gaussian Processes NeurIPS 2018 Variational Message Passing with Structured Inference Networks ICLR 2018 Variational Network Inference: Strong and Stable with Concrete Support ICML 2018 Variational Rejection Sampling AISTATS 2018 Variational Sequential Monte Carlo AISTATS 2018 Wasserstein Variational Inference NeurIPS 2018 Who Learns Better Bayesian Network Structures: Constraint-Based, Score-based or Hybrid Algorithms? PGM 2018 Wrapped Gaussian Process Regression on Riemannian Manifolds CVPR 2018 Z-Transforms and its Inference on Partially Observable Point Processes IJCAI 2018 A Conditional Variational Framework for Dialog Generation ACL 2017 A Covariance Matrix Adaptation Evolution Strategy for Direct Policy Search in Reproducing Kernel Hilbert Space ACML 2017 Active Incremental Learning of Robot Movement Primitives CoRL 2017 ADAPT at IJCNLP-2017 Task 4: A Multinomial Naive Bayes Classification Approach for Customer Feedback Analysis task IJCNLP 2017 Adapting Topic Models using Lexical Associations with Tree Priors EMNLP 2017 A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering NeurIPS 2017 A Functional Dynamic Boltzmann Machine IJCAI 2017 A Generative Parser with a Discriminative Recognition Algorithm ACL 2017 AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms NeurIPS 2017 A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings ACML 2017 An Automatic Approach for Document-level Topic Model Evaluation CoNLL 2017