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Machine Learning ›

Bayesian & Probabilistic

3,963 papers (2 classified directly here)

Subtopics

Probabilistic Modeling (2,252) Variational Inference (802) Gaussian Processes (570) Bayesian Learning (455) Bayesian Optimization (221) Markov Chain Monte Carlo (143) Nonparametric Bayesian (86) Bayesian Networks (81) Conditional Random Fields (5)

Papers per year

9
118
124
394
151
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'25

Papers (including subtopics)

Improving posterior marginal approximations in latent Gaussian models AISTATS 2010
Bayesian variable order Markov models AISTATS 2010
Nonparametric Bayesian Matrix Factorization by Power-EP AISTATS 2010
Neural conditional random fields AISTATS 2010
Graphical Gaussian modelling of multivariate time series with latent variables AISTATS 2010
A Weighted Multi-Sequence Markov Model For Brain Lesion Segmentation AISTATS 2010
Variational methods for Reinforcement Learning AISTATS 2010
On Combining Graph-based Variance Reduction schemes AISTATS 2010
Noise-contrastive estimation: A new estimation principle for unnormalized statistical models AISTATS 2010
Collaborative Filtering via Rating Concentration AISTATS 2010
Maximum-likelihood learning of cumulative distribution functions on graphs AISTATS 2010
Learning Bayesian Network Structure using LP Relaxations AISTATS 2010
Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms AISTATS 2010
Simple Exponential Family PCA AISTATS 2010
Supervised Dimension Reduction Using Bayesian Mixture Modeling AISTATS 2010
Parallelizable Sampling of Markov Random Fields AISTATS 2010
Approximation of hidden Markov models by mixtures of experts with application to particle filtering AISTATS 2010
A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection AISTATS 2010
Bayesian structure discovery in Bayesian networks with less space AISTATS 2010
Identifying Cause and Effect on Discrete Data using Additive Noise Models AISTATS 2010
Infinite Predictor Subspace Models for Multitask Learning AISTATS 2010
Nonparametric prior for adaptive sparsity AISTATS 2010
Gaussian processes with monotonicity information AISTATS 2010
Approximate parameter inference in a stochastic reaction-diffusion model AISTATS 2010
Efficient Learning of Deep Boltzmann Machines AISTATS 2010