← Bayesian & Probabilistic
Artificial Intelligence › Bayesian & Probabilistic ›

Bayesian Learning

1663 directly classified papers

Papers per year

Papers

A neural network implementing optimal state estimation based on dynamic spike train decoding NIPS 2007
Bayesian Co-Training NIPS 2007
Privacy-Preserving Belief Propagation and Sampling NIPS 2007
Comparing Bayesian models for multisensory cue combination without mandatory integration NIPS 2007
The Infinite Markov Model NIPS 2007
TrueSkill Through Time: Revisiting the History of Chess NIPS 2007
Hidden Common Cause Relations in Relational Learning NIPS 2007
Markov Chain Monte Carlo with People NIPS 2007
Efficient Bayesian Inference for Dynamically Changing Graphs NIPS 2007
Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations NIPS 2007
A Bayesian LDA-based model for semi-supervised part-of-speech tagging NIPS 2007
On Sparsity and Overcompleteness in Image Models NIPS 2007
Variational inference for Markov jump processes NIPS 2007
The Infinite Gamma-Poisson Feature Model NIPS 2007
Multi-task Gaussian Process Prediction NIPS 2007
Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes NIPS 2007
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NIPS 2007
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior NIPS 2007
Modeling Dyadic Data with Binary Latent Factors NIPS 2006
Bayesian Policy Gradient Algorithms NIPS 2006
Unified Inference for Variational Bayesian Linear Gaussian State-Space Models NIPS 2006
Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models NIPS 2006
Multiple timescales and uncertainty in motor adaptation NIPS 2006
Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models NIPS 2006
TrueSkill™: A Bayesian Skill Rating System NIPS 2006