Marcus Klasson
I obtained my PhD from KTH in Sweden, where I was supervised by Hedvig Kjellström and Cheng Zhang. After the PhD, I was a postdoc at Aalto University working with Arno Solin and Juho Kannala on uncertainty-aware methods for computer vision topics such as NeRF/GS and VLMs.
Research
I am interested in computer vision, deep learning, various approaches to uncertainty estimation, and their real-world applications where methods must adapt fast under limited supervision and resources.
Here is a selected list of my research publications. See Google Scholar for a full list.
Learn the Time to Learn: Replay Scheduling in Continual Learning
Marcus Klasson, Hedvig Kjellström, Cheng Zhang
TMLR, 2023
Learning schedules over which tasks to replay at different times in continual learning can outperform replaying all tasks equally or using heuristic scheduling rules.
Marcus Klasson, Hedvig Kjellström, Cheng Zhang
TMLR, 2023
Learning schedules over which tasks to replay at different times in continual learning can outperform replaying all tasks equally or using heuristic scheduling rules.
A Hierarchical Grocery Store Image Dataset with Visual and Semantic Labels
Marcus Klasson, Cheng Zhang, Hedvig Kjellström
WACV, 2019
Dataset for grocery item classification with natural images from grocery stores organized with hierarchical labels, where each class has a corresponding web-scraped text and iconic image.
Marcus Klasson, Cheng Zhang, Hedvig Kjellström
WACV, 2019
Dataset for grocery item classification with natural images from grocery stores organized with hierarchical labels, where each class has a corresponding web-scraped text and iconic image.