Thomas Schön

Thomas Schön, Professor of Automatic Control at Uppsala University. Photo: Mikael Wallerstedt

Our aim is to automate the extraction of knowledge and understanding from data. Allowing machines (and humans) to understand what is happening and to acquire new skills and learn new things. We achieve this by developing new probabilistic models and deriving algorithms capable of learnings these models from data. The systematic use of probability in representing and manipulating these models is key. It allows us to represent not only what we know, but to some extent also what we do not know. We take a particular interest in dynamical phenomena evolving over time.

Our research is multi-disciplinary and it sits somewhere on the intersection of the areas of Machine learning and statistics, signal processing, automatic control and computer vision. We pursue both basic and applied research, which explains our tight collaboration with various companies. A slightly more detailed overview of our research is available here.

Recent research results/news

September 14, 2017 [Teaching the SMC methods course in Brussels] I will teach the SMC methods course in Brussels during the time period October 3 - 6, 2017. More complete information about the August edition of the course is available here.

September 12, 2017 [Journal paper accepted for Mechanical Systems and Signal Processing] A particle filtering based algorithm used to identify a nonlinear dynamical system based on observations that are highly informative (observations where there is very little or no measurement noise present) often ends up in trouble. To counteract this we suggest an algorithm which initially assumes that there is artificial measurement noise present. The variance of this noise is sequentially decreased in an adaptive fashion such that we in the end recover the original problem or possibly a very close approximation of it. Computationally the parameters are learned using a sequential Monte Carlo (SMC) sampler. We illustrate the new algorithm on one of the benchmarks for nonlinear system identification avilable here. More specifically we learn a challenging Wiener-Hammerstein system (described here) arising from an electrical circuit.

Andreas Svensson, Thomas B. Schön and Fredrik Lindsten. Learning of state-space models with highly informative observations: a tempered Sequential Monte Carlo solution. Mechanical Systems and Signal Processing (MSSP), 2017. [arXiv]

September 4, 2017 [Paper accepted for NIPS] In this work we present a new probabilistic model in the form of a Gaussian process that is guaranteed to fulfill linear operator constraints. These constraints can for example encode fundamental properties of physics. One of the examples involve modelling of the magnetic field, which is known to be curl-free. This basic knowledge is encoded in our model from the start and as we aquire measurements the model is adapted accordingly. This opens up for exciting opportunities, where we can start from basic scientific laws and then fill in with specific knowledge optained from measurements in the particular situation at hand, in such a way that we at all times properly accounts for uncertainty throughout the entire model.

Carl Jidling, Niklas Wahlström, Adrian Wills and Thomas B. Schön. Linearly constrained Gaussian processesAdvances in Neural Information Processing Systems (NIPS), Long Beach, CA, USA, December, 2017. [arXiv]

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September 1, 2017 [SMC workshop and PhD course] The Sequential Monte Carlo workshop and the associated PhD course are now over. All the material is available from the course and workshop websites. If you are still interested in the PhD course it is offered once more in October, but that time it is given in Brussels, Belgium. More information will be available here shortly.

August 23, 2017 [SMC PhD course starting tomorrow] Tomorrow we start the intensive PhD course on SMC methods here in Uppsala. There are 85 students registered for the course, from 13 countries representing 35  universities and companies. More information about the course is available here. Directly after the course we are hosting the international conference on SMC at Norrlands Nation here in Uppsala with roughly 100 participants, more information about this event is available here.

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 © Thomas Schön 2017