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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

ELFI: Engine for Likelihood-Free Inference JMLR 2018
Label-Sensitive Task Grouping by Bayesian Nonparametric Approach for Multi-Task Multi-Label Learning IJCAI 2018
Instance-Specific Bayesian Network Structure Learning PGM 2018
Learning Bayesian network classifiers with completed partially directed acyclic graphs PGM 2018
Learning Bayesian Networks by Branching on Constraints PGM 2018
Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences AISTATS 2018
Approximate Bayesian Computation with Kullback-Leibler Divergence as Data Discrepancy AISTATS 2018
Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation CORL 2018
Probabilistic preference learning with the Mallows rank model JMLR 2018
Double Joint Bayesian Modeling of DNN Local I-Vector for Text Dependent Speaker Verification with Random Digit Strings INTERSPEECH 2018
Latent Factor Analysis of Deep Bottleneck Features for Speaker Verification with Random Digit Strings INTERSPEECH 2018
Category-aware Next Point-of-Interest Recommendation via Listwise Bayesian Personalized Ranking IJCAI 2017
Soft-Bayes: Prod for Mixtures of Experts with Log-Loss ALT 2017
An Empirical Bayes Approach to Optimizing Machine Learning Algorithms NIPS 2017
Time for a Change: a Tutorial for Comparing Multiple Classifiers Through Bayesian Analysis JMLR 2017
Differential Privacy for Bayesian Inference through Posterior Sampling JMLR 2017
Gray-box Inference for Structured Gaussian Process Models AISTATS 2017
Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks NIPS 2017
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders NIPS 2017
Probabilistic Line Searches for Stochastic Optimization JMLR 2017
Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons NIPS 2017
Flexible statistical inference for mechanistic models of neural dynamics NIPS 2017
Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models JMLR 2017
A Bayesian Framework for Learning Rule Sets for Interpretable Classification JMLR 2017
Information-theoretic limits of Bayesian network structure learning AISTATS 2017