Stochastic Processes

Mass Fatality Incident Identification based on nuclear DNA evidence AISTATS 2010 Mean Field Variational Approximation for Continuous-Time Bayesian Networks JMLR 2010 Mixture of time-warped trajectory models for movement decoding NeurIPS 2010 On Finding Predictors for Arbitrary Families of Processes JMLR 2010 Parallelizable Sampling of Markov Random Fields AISTATS 2010 Parametric Herding AISTATS 2010 Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models NeurIPS 2010 Risk Bounds for Levy Processes in the PAC-Learning Framework AISTATS 2010 Stability Bounds for Stationary φ-mixing and β-mixing Processes JMLR 2010 State-Space Inference and Learning with Gaussian Processes AISTATS 2010 Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines AISTATS 2010 A joint maximum-entropy model for binary neural population patterns and continuous signals NeurIPS 2009 A Stochastic approximation method for inference in probabilistic graphical models NeurIPS 2009 Bootstrapping from Game Tree Search NeurIPS 2009 Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation NeurIPS 2009 Fast Learning from Non-i.i.d. Observations NeurIPS 2009 Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation NeurIPS 2009 Improving Existing Fault Recovery Policies NeurIPS 2009 Indian Buffet Processes with Power-law Behavior NeurIPS 2009 Know Thy Neighbour: A Normative Theory of Synaptic Depression NeurIPS 2009 Learning in Markov Random Fields using Tempered Transitions NeurIPS 2009 Maximum likelihood trajectories for continuous-time Markov chains NeurIPS 2009 Perceptual Multistability as Markov Chain Monte Carlo Inference NeurIPS 2009 Perturbation Corrections in Approximate Inference: Mixture Modelling Applications JMLR 2009 Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory NeurIPS 2009