Bayesian & Probabilistic

Probabilistic Video Prediction From Noisy Data With a Posterior Confidence CVPR 2020 ProbAnch: a Modular Probabilistic Anchoring Framework IJCAI 2020 Projected Stein Variational Gradient Descent NeurIPS 2020 Public Sentiment Drift Analysis Based on Hierarchical Variational Auto-encoder EMNLP 2020 Quantile Graphical Models: a Bayesian Approach JMLR 2020 Quantile Propagation for Wasserstein-Approximate Gaussian Processes NeurIPS 2020 Quantum Probabilistic Models Using Feynman Diagram Rules for Better Understanding the Information Diffusion Dynamics in Online Social Networks AAAI 2020 Radial and Directional Posteriors for Bayesian Deep Learning AAAI 2020 Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning AISTATS 2020 Randomly Projected Additive Gaussian Processes for Regression ICML 2020 Reasoning about Uncertainties in Discrete-Time Dynamical Systems using Polynomial Forms. NeurIPS 2020 Reconsidering Generative Objectives For Counterfactual Reasoning NeurIPS 2020 Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling IJCAI 2020 Relation-Based Counterfactual Explanations for Bayesian Network Classifiers IJCAI 2020 Replica-Exchange Nos\'e-Hoover Dynamics for Bayesian Learning on Large Datasets NeurIPS 2020 Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference EMNLP 2020 Residual Neural Processes AAAI 2020 Riemannian Continuous Normalizing Flows NeurIPS 2020 RIJP at SemEval-2020 Task 1: Gaussian-based Embeddings for Semantic Change Detection SemEval 2020 Robust, Accurate Stochastic Optimization for Variational Inference NeurIPS 2020 Robustness of Bayesian Neural Networks to Gradient-Based Attacks NeurIPS 2020 Robust Optimisation Monte Carlo AISTATS 2020 Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences ICML 2020 Sampling-Free Learning of Bayesian Quantized Neural Networks ICLR 2020 Scalable and Efficient Comparison-based Search without Features ICML 2020