Skip to main content
Department of Information Technology

Video material

Within ASSEMBLE we are producing short 3 min. videos on selected research results with the intention of offering easy access to the research results produced within the project. For all the details, the corresponding paper is linked in connection to the video itself.

Jan Kudlicka: Probabilistic programming for birth-death models of evolution using an alive particle filter with delayed sampling

Jan Kudlicka, Lawrence M. Murray, Fredrik Ronquist and Thomas B. Schön. Probabilistic programming for birth-death models of evolution using an alive particle filter with delayed sampling. In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), Tel Aviv, Israel, July, 2019. arXiv

Ricardo Alves: Filter Caching for Free: The Untapped Potential of the Store-Buffer

Ricardo Alves, Alberto Ros, David Black-Schaffer, Stefanos Kaxiras . Filter Caching for Free: The Untapped Potential of the Store Buffer. 46th International Symposium on Computer Architecture (ISCA), Phoenix, AZ (USA), June 2019. diva

Daniel Lundén: Automatic Alignment of Sequential Monte Carlo Inference in Higher-Order Probabilistic Programs

Daniel Lundén, David Broman, Fredrik Ronquist, Lawrence M. Murray. Automatic Alignment of Sequential Monte Carlo Inference in Higher-Order Probabilistic Programs. arXiv

Joakim Jaldén: Alternative EM Algorithms for Nonlinear State Space Models

Johan Wahlström, Joakim Jaldén, Isaac Skog and Peter Händel. Alternative EM Algorithms for Nonlinear State-Space Models. 21st International Conference on Information Fusion (FUSION), IEEE, 2018.

Jack Umenberger: Learning convex bounds for linear quadratic control policy synthesis

Jack Umenberger and Thomas B. Schön. Learning convex bounds for linear quadratic control policy synthesis. In Neural Information Processing Systems (NIPS), Montréal, Canada, December 2018. NeurIPS

Carl Jidling: Linearly constrained Gaussian processes

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

Updated  2020-03-23 11:36:52 by Carl Jidling.