state space model

Computationally Efficient Bayesian Learning of Gaussian Process State Space Models AISTATS 2016 Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case PGM 2016 Learning to Filter with Predictive State Inference Machines ICML 2016 Sequential Neural Models with Stochastic Layers NeurIPS 2016 The Nonparametric Kernel Bayes Smoother AISTATS 2016 JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes ICML 2015 Neural Adaptive Sequential Monte Carlo NeurIPS 2015 State Space Methods for Efficient Inference in Student-t Process Regression AISTATS 2015 A State-Space Model for Decoding Auditory Attentional Modulation from MEG in a Competing-Speaker Environment NeurIPS 2014 Bayesian Switching Interaction Analysis Under Uncertainty AISTATS 2014 Explicit Link Between Periodic Covariance Functions and State Space Models AISTATS 2014 Particle Gibbs with Ancestor Sampling JMLR 2014 Variational Gaussian Process State-Space Models NeurIPS 2014 Approximate inference in latent Gaussian-Markov models from continuous time observations NeurIPS 2013 Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC NeurIPS 2013 Multilinear Dynamical Systems for Tensor Time Series NeurIPS 2013 A Marginalized Particle Gaussian Process Regression NeurIPS 2012 Ancestor Sampling for Particle Gibbs NeurIPS 2012 Fast interior-point inference in high-dimensional sparse, penalized state-space models AISTATS 2012 Infinite-Dimensional Kalman Filtering Approach to Spatio-Temporal Gaussian Process Regression AISTATS 2012 A General Linear Non-Gaussian State-Space Model: Identifiability, Identification, and Applications ACML 2011 Directional Statistics on Permutations AISTATS 2011 Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron NeurIPS 2011 Switch-Reset Models : Exact and Approximate Inference AISTATS 2011 Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes JMLR 2010