variational inference

Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning AISTATS 2020 Reconsidering Generative Objectives For Counterfactual Reasoning NeurIPS 2020 Reconstructing continuous distributions of 3D protein structure from cryo-EM images ICLR 2020 Recurrent Hierarchical Topic-Guided RNN for Language Generation ICML 2020 Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations NeurIPS 2020 Regularized Wasserstein Means for Aligning Distributional Data AAAI 2020 Replica-Exchange Nos\'e-Hoover Dynamics for Bayesian Learning on Large Datasets NeurIPS 2020 Residual Neural Processes AAAI 2020 Robust, Accurate Stochastic Optimization for Variational Inference NeurIPS 2020 Robust Data Programming with Precision-guided Labeling Functions AAAI 2020 Robustness of Bayesian Neural Networks to Gradient-Based Attacks NeurIPS 2020 Scalable Approximate MCMC Algorithms for the Horseshoe Prior JMLR 2020 Scalable Exact Inference in Multi-Output Gaussian Processes ICML 2020 Scalable Gaussian Process Regression Networks IJCAI 2020 Scalable Inference on the Soft Affiliation Graph Model for Overlapping Community Detection ACML 2020 Scalable Nonparametric Factorization for High-Order Interaction Events AISTATS 2020 Scalable Uncertainty for Computer Vision With Functional Variational Inference CVPR 2020 Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression AAAI 2020 Self-Modulating Nonparametric Event-Tensor Factorization ICML 2020 Self-Paced Deep Reinforcement Learning NeurIPS 2020 Semi-supervised Sequential Generative Models UAI 2020 Single Episode Policy Transfer in Reinforcement Learning ICLR 2020 Social-VRNN: One-Shot Multi-modal Trajectory Prediction for Interacting Pedestrians CoRL 2020 Sparse Gaussian Processes with Spherical Harmonic Features ICML 2020 Specializing Word Embeddings (for Parsing) by Information Bottleneck (Extended Abstract) IJCAI 2020