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Artificial Intelligence

72,274 papers (0 classified directly here)

Subtopics

Core AI (59,089) Learning Paradigms (14,108) Bayesian & Probabilistic (4,335)

Papers per year

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14833
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Papers (including subtopics)

Reduced-Rank Hidden Markov Models AISTATS 2010
Nonparametric Tree Graphical Models AISTATS 2010
Inference and Learning in Networks of Queues AISTATS 2010
HOP-MAP: Efficient Message Passing with High Order Potentials AISTATS 2010
Bayesian Gaussian Process Latent Variable Model AISTATS 2010
A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping AISTATS 2010
Learning Causal Structure from Overlapping Variable Sets AISTATS 2010
State-Space Inference and Learning with Gaussian Processes AISTATS 2010
Sequential Monte Carlo Samplers for Dirichlet Process Mixtures AISTATS 2010
Modeling annotator expertise: Learning when everybody knows a bit of something AISTATS 2010
Multi-Task Learning using Generalized t Process AISTATS 2010
Matrix-Variate Dirichlet Process Mixture Models AISTATS 2010
An Efficient Explanation of Individual Classifications using Game Theory JMLR 2010
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation JMLR 2010
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions JMLR 2010
Optimal Search on Clustered Structural Constraint for Learning Bayesian Network Structure JMLR 2010
Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting JMLR 2010
On Spectral Learning JMLR 2010
Continuous Time Bayesian Network Reasoning and Learning Engine JMLR 2010
Approximate Inference on Planar Graphs using Loop Calculus and Belief Propagation JMLR 2010
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity JMLR 2010
FastInf: An Efficient Approximate Inference Library JMLR 2010
Evolving Static Representations for Task Transfer JMLR 2010
Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing JMLR 2010
How to Explain Individual Classification Decisions JMLR 2010