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Bayesian Learning

1,663 papers

Papers per year

2
48
52
137
36
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Papers

Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models NIPS 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
Incremental Variational Sparse Gaussian Process Regression NIPS 2016
Bayesian Optimization for Probabilistic Programs NIPS 2016
A Probabilistic Programming Approach To Probabilistic Data Analysis NIPS 2016
Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model NIPS 2016
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NIPS 2016
Bayesian latent structure discovery from multi-neuron recordings NIPS 2016
Poisson-Gamma dynamical systems NIPS 2016
Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making NIPS 2016
Batched Gaussian Process Bandit Optimization via Determinantal Point Processes NIPS 2016
Differential Privacy without Sensitivity NIPS 2016
Bayesian Optimization with Robust Bayesian Neural Networks NIPS 2016
Sampling for Bayesian Program Learning NIPS 2016
Observational-Interventional Priors for Dose-Response Learning NIPS 2016
Kernel Bayesian Inference with Posterior Regularization NIPS 2016
Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables NIPS 2016
Gaussian Processes for Survival Analysis NIPS 2016
Natural-Parameter Networks: A Class of Probabilistic Neural Networks NIPS 2016
Scalable Structure Discovery in Regression using Gaussian Processes AUTOML 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
K2-ABC: Approximate Bayesian Computation with Kernel Embeddings AISTATS 2016