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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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Papers (including subtopics)

Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching AISTATS 2010
Dense Message Passing for Sparse Principal Component Analysis AISTATS 2010
Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks AISTATS 2010
On the Convergence Properties of Contrastive Divergence AISTATS 2010
Inference and Learning in Networks of Queues AISTATS 2010
HOP-MAP: Efficient Message Passing with High Order Potentials AISTATS 2010
Unsupervised Aggregation for Classification Problems with Large Numbers of Categories AISTATS 2010
Bayesian Gaussian Process Latent Variable Model AISTATS 2010
State-Space Inference and Learning with Gaussian Processes AISTATS 2010
Sequential Monte Carlo Samplers for Dirichlet Process Mixtures AISTATS 2010
An Alternative Prior Process for Nonparametric Bayesian Clustering AISTATS 2010
Dependent Indian Buffet Processes AISTATS 2010
Modeling annotator expertise: Learning when everybody knows a bit of something AISTATS 2010
Multi-Task Learning using Generalized t Process AISTATS 2010
Bayesian Generalized Kernel Models AISTATS 2010
Matrix-Variate Dirichlet Process Mixture Models AISTATS 2010
Learning models of object structure NIPS 2009
Spatial Normalized Gamma Processes NIPS 2009
Multi-Label Prediction via Sparse Infinite CCA NIPS 2009
Rethinking LDA: Why Priors Matter NIPS 2009
Non-stationary continuous dynamic Bayesian networks NIPS 2009
Gaussian process regression with Student-t likelihood NIPS 2009
Sensitivity analysis in HMMs with application to likelihood maximization NIPS 2009
Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution NIPS 2009
A Stochastic approximation method for inference in probabilistic graphical models NIPS 2009