My main research interest is nonlinear inference, especially within the context of dynamical systems, solved using probabilistic models and algorithms. In terms of scientific fields, my research is situated somewhere on the intersection between the fields of machine learning, signal processing and automatic control. My aim is to pursue both basic and applied research, where the latter is typically carried out in close collaboration with industry. A brief overview of my research is available here and my publications are available here.
Recent research results/news
September 22, 2014: Our new derivation of recursive direct weight optimization has been accepted for publication in IEEE TAC
Liang Dai and Thomas B. Schön. A new structure exploiting derivation of recursive direct weight optimization. IEEE Transactions on Automatic Control, 2014. (accepted for publication)
September 9, 2014: Our paper on inference in general probabilistic graphical models has been accepted for publication at NIPS 2014. Our method is consistent and it provides unbiased estimates of the partition function. I gave a seminar on the idea at the Isaac Newton Institute for Mathematical Sciences in Cambridge earlier this year, the talk is available here.
Christian A. Naesseth, Fredrik Lindsten and Thomas B. Schön. Sequential Monte Carlo methods for graphical models. Advances in Neural Information Processing Systems (NIPS) 27, Montreal, Quebec, Canada, December, 2014. [pdf] [arXiv] [code] [video]
September 8, 2014: Johan Dahlin just started his pre-doc at the University of New South Wales (UNSW) in Sydney, Australia. He hosts are Robert Kohn at the Australian School of Business and Pierre Del Moral at the School of Mathematics and Statistics.
September 4, 2014: I am very glad to announce that Tobias Rydén will join us as an Adjunct Professor. Tobias main employer is Lynx Asset Management and he has perviously held Professor positions (mathematical statistics) at Lund University and KTH.
August 29, 2014: Received the Automatica best paper award for papers published in Automatica 2011-2013, link. Awarded for the paper; Thomas B. Schön, Adrian Wills and Brett Ninness. System identification of nonlinear state-space models. Automatica, 47(1):39-49, January 2011. [pdf] The award was handed out at the 18th World Congress of the International Federation of Automatic Control (IFAC), Cape Town, South Africa, August, 2014, where we also received a honorable mention (nominated for the best application paper award) with the paper Manon Kok, Jeroen D. Hol and Thomas B. Schön. An optimization-based approach to human body motion capture using inertial sensors. [pdf]
August 28, 2014: Our new results on Bayesian parameter inference in nonlinear dynamical systems have just been accepted for publication in Statistics and Computing. We introduce two alternative versions of the Particle Metropolis Hastings (PMH) algorithm that incorporate gradient and Hessian information about the posterior into the proposal. In the paper we show how to estimate the required information using a fixed-lag particle smoother.
Johan Dahlin, Fredrik Lindsten and Thomas B. Schön. Particle Metropolis Hastings using gradient and Hessian information. Statistics and Computing, 2014. (accepted for publication) [pdf] [arXiv] [code]
August 22, 2014: Christian Andersson Naesseth won the best poster award at the Summer school on deep learning for image analysis (held in Copenhagen, Denmark). The poster is available here and the papers describing the work in detail are available here and here.
August 18, 2014: During the summer a team of students have been working on realizing the CARS project, which is an acronym for Camera-based Autonomous Racing System. You can have a look at their result in this video. It includes a camera based target tracking system, controllers and of course the practical implemention of it all. The project web-site will be available shortly.
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