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Fredrik Lindsten

Senior Associate Professor, Head of Division, Head of Unit

I am developing tools that can be used to extract valuable information from complex data sets. I am particularly interested in methods that can quantify and enable reasoning about the uncertainty associated with essentially all data.

I am an Associate Professor at the Division of Statistics and Machine Learning, Linköping University, Sweden.

I am interested in the interplay between statistics and machine learning, in particular how statistical methodology can be used to quantify and reason about the uncertainties in the predictions and decisions made by machine learning systems.

For more information, please see my external web page.



Johannes Varga, Emil Karlsson, Günther R. Raidl, Elina Rönnberg, Fredrik Lindsten, Tobias Rodemann (2023) Speeding Up Logic-Based Benders Decomposition by Strengthening Cuts with Graph Neural Networks Machine Learning, Optimization, and Data Science, p. 24-38 Continue to DOI
Joel Oskarsson, Sidén Per, Fredrik Lindsten (2023) Temporal Graph Neural Networks for Irregular Data Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, p. 4515-4531
Amirhossein Ahmadian, Fredrik Lindsten (2023) Enhancing Representation Learning with Deep Classifiers in Presence of Shortcut Proceedings of IEEE ICASSP 2023 Continue to DOI
Amanda Olmin, Jakob Lindqvist, Lennart Svensson, Fredrik Lindsten (2023) Active Learning with Weak Supervision for Gaussian Processes Neural Information Processing 29th International Conference, ICONIP 2022, Virtual Event, November 22–26, 2022, Proceedings, Part V, p. 195-204 Continue to DOI


Joel Oskarsson, Per Sidén, Fredrik Lindsten (2022) Scalable Deep Gaussian Markov Random Fields for General Graphs Proceedings of the 39th International Conference on Machine Learning, p. 17117-17137



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