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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Stein Variational Gradient Descent With Matrix-Valued Kernels NIPS 2019
Gradient-based Adaptive Markov Chain Monte Carlo NIPS 2019
Thompson Sampling for Multinomial Logit Contextual Bandits NIPS 2019
Multi-task Learning for Aggregated Data using Gaussian Processes NIPS 2019
Offline Contextual Bayesian Optimization NIPS 2019
Variational Russian Roulette for Deep Bayesian Nonparametrics ICML 2019
What's to Know? Uncertainty as a Guide to Asking Goal-Oriented Questions CVPR 2019
Bayesian Hierarchical Dynamic Model for Human Action Recognition CVPR 2019
Generalizing Eye Tracking With Bayesian Adversarial Learning CVPR 2019
Importance Weighted Hierarchical Variational Inference NIPS 2019
Iterative Bayesian Learning for Crowdsourced Regression AISTATS 2019
Adaptive Thompson Sampling Stacks for Memory Bounded Open-Loop Planning IJCAI 2019
Efficient Bayesian Optimization for Target Vector Estimation AISTATS 2019
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design AISTATS 2019
Locally Private Bayesian Inference for Count Models ICML 2019
Bayesian Joint Estimation of Multiple Graphical Models NIPS 2019
Band-Limited Gaussian Processes: The Sinc Kernel NIPS 2019
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups AISTATS 2018
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization ICML 2018
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection ICML 2018
Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design ICML 2018
Bayesian Model Selection for Change Point Detection and Clustering ICML 2018
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks NIPS 2018
Scalable Hyperparameter Transfer Learning NIPS 2018
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data NIPS 2018