Fredrik Lindsten

Senior Associate Professor, Head of Division

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.

Publications

2024

Patrick E. Konold, Leonardo Monrroy, Alfredo Bellisario, Diogo Filipe, Patrick Adams, Roberto Alvarez, Richard Bean, Johan Bielecki, Szabolcs Bodizs, Gabriel Ducrocq, Helmut Grubmueller, Richard A. Kirian, Marco Kloos, Jayanath C. P. Koliyadu, Faisal H. M. Koua, Taru Larkiala, Romain Letrun, Fredrik Lindsten, Michael Maihöfer, Andrew V. Martin, Petra Meszaros, Jennifer Mutisya, Amke Nimmrich, Kenta Okamoto, Adam Round, Tokushi Sato, Joana Valerio, Daniel Westphal, August Wollter, Tej Varma Yenupuri, Tong You, Filipe Maia, Sebastian Westenhoff (2024) Microsecond time-resolved X-ray scattering by utilizing MHz repetition rate at second-generation XFELs Nature Methods, Vol. 21, p. 1608-1611 (Article in journal)

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Amanda Olmin, Jakob Lindqvist, Lennart Svensson, Fredrik Lindsten (2024) On the connection between Noise-Contrastive Estimation and Contrastive Divergence INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 238, p. 3016-3024 (Conference paper)

Filip Ekström Kelvinius, Fredrik Lindsten (2024) Discriminator Guidance for Autoregressive Diffusion Models Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, p. 3403-3411 (Conference paper)

Amirhossein Ahmadian, Yifan Ding, Gabriel Eilertsen, Fredrik Lindsten (2024) Unsupervised Novelty Detection in Pretrained Representation Space with Locally Adapted Likelihood Ratio International Conference on Artificial Intelligence and Statistics 2024, Proceedings of Machine Learning Research (Conference paper)

Johannes Varga, Emil Karlsson, Günther R. Raidl, Elina Rönnberg, Fredrik Lindsten, Tobias Rodemann (2024) Speeding Up Logic-Based Benders Decomposition by Strengthening Cuts with Graph Neural Networks Machine Learning, Optimization, and Data Science, p. 24-38 (Conference paper)

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Research

robot dog Spot, drone, small helicopter, operator

WASP at Department of Computer and Information Science (IDA)

WASP, Wallenberg AI autonomous systems and software program, is the largest individual research investment in Sweden in modern times. One of the WASP research environments at LiU is located at the Department of Computer and Information Science.

News

Two men and a woman talk in front of a screen

Machine learning can give the climate a chance

Machine learning can help us discover new patterns and better tackle the climate crisis. Researchers from all over the world meet at Linköping University with the goal of finding and deepening collaborations in this area.

Among the world’s 36 best in machine learning

Fredrik Lindsten and his PhD student Anna Wigren have been chosen among stiff competition to present results at the world’s most prestigious conference in machine learning. One application of their algorithms is to understand how diseases spread.

About the Division

The Division of Statistics and Machine Learning (STIMA)

The STIMA division is part of the Department of Computer and Information Science. The research and teaching activities are focused on modern data analysis and the division hosts the international master's programme in Statistics and Machine Learning.

Staff at STIMA

Senior Associate Professor

Filip Ekström Kelvinius

PhD student

Hariprasath Govindarajan

Anders Grimvall

Ann-Charlotte Hallberg

Woodrow Hao Chi Kiang

Professor, Head of Unit

Shashi Nagarajan

Anders Nordgaard

Adjunct Associate Professor, Docent

Senior Associate Professor, Head of Unit

Jolanta Pielaszkiewicz

Senior Associate Professor

Associate Professor, Docent

Zheng Zhao

Assistant Professor

About the Department

Department of Computer and Information Science (IDA)

The Department of Computer and Information Science is one of the largest departments in northern Europe in its field. Research activity covers artificial intelligence, human-computer interaction, software and computer systems, and data science.

Fredrik Lindsten

Publications

2024

Research

WASP at Department of Computer and Information Science (IDA)

News

Machine learning can give the climate a chance

Among the world’s 36 best in machine learning

About the Division

The Division of Statistics and Machine Learning (STIMA)

Staff at STIMA

About the Department

Department of Computer and Information Science (IDA)

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