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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Enumerating Equivalence Classes of Bayesian Networks using EC Graphs AISTATS 2016
The Factorized Self-Controlled Case Series Method: An Approach for Estimating the Effects of Many Drugs on Many Outcomes JMLR 2016
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models NIPS 2016
Learning under uncertainty: a comparison between R-W and Bayesian approach NIPS 2016
Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables AISTATS 2016
CRAFT: ClusteR-specific Assorted Feature selecTion AISTATS 2016
Bayesian Markov Blanket Estimation AISTATS 2016
A Gibbs Sampler for Learning DAGs JMLR 2016
Bayesian Decision Process for Cost-Efficient Dynamic Ranking via Crowdsourcing JMLR 2016
Dual Control for Approximate Bayesian Reinforcement Learning JMLR 2016
Structure Discovery in Bayesian Networks by Sampling Partial Orders JMLR 2016
Stability of Controllers for Gaussian Process Forward Models ICML 2016
Interactive Bayesian Hierarchical Clustering ICML 2016
Assessing Idiosyncrasies in a Bayesian Model of Speech Communication INTERSPEECH 2016
Bayesian Modeling in Speech Motor Control: A Principled Structure for the Integration of Various Constraints INTERSPEECH 2016
Incremental Variational Sparse Gaussian Process Regression NIPS 2016
Bayesian Optimization for Probabilistic Programs NIPS 2016
Sampling for Bayesian Program Learning NIPS 2016
Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models NIPS 2016
Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model NIPS 2016
Eliciting Categorical Data for Optimal Aggregation NIPS 2016
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NIPS 2016
Poisson-Gamma dynamical systems NIPS 2016
Observational-Interventional Priors for Dose-Response Learning NIPS 2016
Gaussian Processes for Survival Analysis NIPS 2016