← Bayesian & Probabilistic
Machine Learning › Bayesian & Probabilistic ›

Bayesian Inference

1724 directly classified papers

Papers per year

Papers

Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs NIPS 2019
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models NIPS 2019
Alleviating Label Switching with Optimal Transport NIPS 2019
Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction NIPS 2019
Band-Limited Gaussian Processes: The Sinc Kernel NIPS 2019
The Functional Neural Process NIPS 2019
Pseudo-Extended Markov chain Monte Carlo NIPS 2019
Thompson Sampling with Information Relaxation Penalties NIPS 2019
Statistical Model Aggregation via Parameter Matching NIPS 2019
Thompson Sampling and Approximate Inference NIPS 2019
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters NIPS 2019
Differentially Private Bayesian Linear Regression NIPS 2019
Computational Separations between Sampling and Optimization NIPS 2019
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing NIPS 2018
Parsimonious Bayesian deep networks NIPS 2018
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo NIPS 2018
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds NIPS 2018
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits NIPS 2018
Efficient inference for time-varying behavior during learning NIPS 2018
Scalar Posterior Sampling with Applications NIPS 2018
Lifted Weighted Mini-Bucket NIPS 2018
Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach NIPS 2018
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification NIPS 2018
Statistical mechanics of low-rank tensor decomposition NIPS 2018
Fast Estimation of Causal Interactions using Wold Processes NIPS 2018