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Stochastic Processes

2667 directly classified papers

Papers per year

Papers

State-Space Inference and Learning with Gaussian Processes AISTATS 2010
Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning NIPS 2010
Dependent Indian Buffet Processes AISTATS 2010
Learning the Structure of Deep Sparse Graphical Models AISTATS 2010
Mixture of time-warped trajectory models for movement decoding NIPS 2010
Identifying graph-structured activation patterns in networks NIPS 2010
Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains NIPS 2010
Gaussian sampling by local perturbations NIPS 2010
Fractionally Predictive Spiking Neurons NIPS 2010
Approximate parameter inference in a stochastic reaction-diffusion model AISTATS 2010
Risk Bounds for Levy Processes in the PAC-Learning Framework AISTATS 2010
Learning Networks of Stochastic Differential Equations NIPS 2010
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines AISTATS 2010
Parallelizable Sampling of Markov Random Fields AISTATS 2010
Belief space planning assuming maximum likelihood observations RSS 2010
Mean Field Variational Approximation for Continuous-Time Bayesian Networks JMLR 2010
Parametric Herding AISTATS 2010
Effects of Synaptic Weight Diffusion on Learning in Decision Making Networks NIPS 2010
Dynamic Infinite Relational Model for Time-varying Relational Data Analysis NIPS 2010
Linear readout from a neural population with partial correlation data NIPS 2010
Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices NIPS 2010
Mass Fatality Incident Identification based on nuclear DNA evidence AISTATS 2010
A highly efficient blocked Gibbs sampler reconstruction of multidimensional NMR spectra AISTATS 2010
Functional form of motion priors in human motion perception NIPS 2010
Bayesian variable order Markov models AISTATS 2010