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Probabilistic Modeling

2591 directly classified papers

Papers per year

Papers

Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora NIPS 2009
Bayesian Nonparametric Models on Decomposable Graphs NIPS 2009
Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process NIPS 2009
Sparse and Locally Constant Gaussian Graphical Models NIPS 2009
An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism NIPS 2009
Modeling the spacing effect in sequential category learning NIPS 2009
A Stochastic approximation method for inference in probabilistic graphical models NIPS 2009
Gaussian process regression with Student-t likelihood NIPS 2009
Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions NIPS 2009
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features NIPS 2009
Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies NIPS 2009
Which graphical models are difficult to learn? NIPS 2009
Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning NIPS 2009
Rethinking LDA: Why Priors Matter NIPS 2009
Learning models of object structure NIPS 2009
Sparse Convolved Gaussian Processes for Multi-output Regression NIPS 2008
Multi-task Gaussian Process Learning of Robot Inverse Dynamics NIPS 2008
Probabilistic detection of short events, with application to critical care monitoring NIPS 2008
Learning Transformational Invariants from Natural Movies NIPS 2008
Characterizing response behavior in multisensory perception with conflicting cues NIPS 2008
A mixture model for the evolution of gene expression in non-homogeneous datasets NIPS 2008
Temporal Dynamics of Cognitive Control NIPS 2008
Bayesian Network Score Approximation using a Metagraph Kernel NIPS 2008
Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex NIPS 2008
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM NIPS 2008