Bayesian Inference

Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization NeurIPS 2020 Regret Bound for Safe Gaussian Process Bandit Optimization L4DC 2020 Regularized Gaussian Belief Propagation with Nodes of Arbitrary Size JMLR 2020 Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference EMNLP 2020 Residual Neural Processes AAAI 2020 Restarted Bayesian Online Change-point Detector achieves Optimal Detection Delay ICML 2020 Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice NeurIPS 2020 Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes NeurIPS 2020 Robust, Accurate Stochastic Optimization for Variational Inference NeurIPS 2020 Robust Bayesian Classification Using An Optimistic Score Ratio ICML 2020 Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation AAAI 2020 Robust Optimisation Monte Carlo AISTATS 2020 Robust Reinforcement Learning for Continuous Control with Model Misspecification ICLR 2020 Safe-Bayesian Generalized Linear Regression AISTATS 2020 Scalable Approximate MCMC Algorithms for the Horseshoe Prior JMLR 2020 Scalable Belief Propagation via Relaxed Scheduling NeurIPS 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 Probabilistic Matrix Factorization with Graph-Based Priors AAAI 2020 Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression AAAI 2020 Second Order PAC-Bayesian Bounds for the Weighted Majority Vote NeurIPS 2020 Selective Dyna-Style Planning Under Limited Model Capacity ICML 2020 Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components AISTATS 2020