Bayesian Inference

Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering ACL 2020 Probabilistic Circuits for Variational Inference in Discrete Graphical Models NeurIPS 2020 Probabilistic Inference for Predicate Constraint Satisfaction AAAI 2020 Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations NeurIPS 2020 Probabilistic Linear Solvers for Machine Learning NeurIPS 2020 Probabilistic Pixel-Adaptive Refinement Networks CVPR 2020 Probabilistic Regression for Visual Tracking CVPR 2020 Probabilistic Safety for Bayesian Neural Networks UAI 2020 Probabilistic Super Resolution for Mineral Spectroscopy AAAI 2020 Probabilistic Video Prediction From Noisy Data With a Posterior Confidence CVPR 2020 Projective Preferential Bayesian Optimization ICML 2020 Provable Smoothness Guarantees for Black-Box Variational Inference ICML 2020 Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel ICLR 2020 Quantile Graphical Models: a Bayesian Approach JMLR 2020 Quantized Variational Inference NeurIPS 2020 R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games ICML 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 Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization ICML 2020 Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation IJCAI 2020 Recalibrating classifiers for interpretable abusive content detection EMNLP 2020 Recovering Causal Structures from Low-Order Conditional Independencies AAAI 2020 Recurrent Hierarchical Topic-Guided RNN for Language Generation ICML 2020 Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations NeurIPS 2020 Recursively Binary Modification Model for Nested Named Entity Recognition AAAI 2020