F
Fredrik Lindsten
Researcher at Linköping University
Publications - 132
Citations - 3077
Fredrik Lindsten is an academic researcher from Linköping University. The author has contributed to research in topics: Particle filter & Markov chain Monte Carlo. The author has an hindex of 30, co-authored 120 publications receiving 2601 citations. Previous affiliations of Fredrik Lindsten include Uppsala University & University of Cambridge.
Papers
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Particle Gibbs with Ancestor Sampling
TL;DR: Particle Markov chain Monte Carlo (PMCMC) as discussed by the authors is a systematic way of combining the two main tools used for Monte Carlo statistical inference: SMC and MCMC.
Journal ArticleDOI
Particle gibbs with ancestor sampling
TL;DR: PGAS provides the data analyst with an off-the-shelf class of Markov kernels that can be used to simulate, for instance, the typically high-dimensional and highly autocorrelated state trajectory in a state-space model.
Book
Backward Simulation Methods for Monte Carlo Statistical Inference
Fredrik Lindsten,Thomas B. Schön +1 more
TL;DR: This tutorial reviews and discusses several related backward-simulation-based methods for state inference as well as learning of static parameters, both using a frequentistic and a Bayesian approach.
Posted Content
Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC
TL;DR: This work presents a fully Bayesian approach to inference and learning in nonlinear nonparametric state-space models and places a Gaussian process prior over the state transition dynamics, resulting in a flexible model able to capture complex dynamical phenomena.
Proceedings ArticleDOI
Clustering using sum-of-norms regularization: With application to particle filter output computation
TL;DR: A novel clustering method that uses a sum-of-norms (SON) regularization to control the tradeoff between the model fit and the number of clusters is presented, formulated as a convex optimization problem.