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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.



Amanda Olmin, Jakob Lindqvist, Lennart Svensson, Fredrik Lindsten (2024) On the connection between Noise-Contrastive Estimation and Contrastive Divergence
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
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


Jakob Lindqvist, Amanda Olmin, Lennart Svensson, Fredrik Lindsten (2023) Generalised Active Learning With Annotation Quality Selection IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP) Continue to DOI
Pierre Glaser, David Widmann, Fredrik Lindsten, Arthur Gretton (2023) Fast and Scalable Score-Based Kernel Calibration Tests Thirty-Ninth Conference on Uncertainty in Artificial Intelligence: PMLR 216



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