Advanced School for Computing and Imaging (ASCI)

ASCI office
Delft University of Technology
Building 28, room 04.E120
Van Mourik Broekmanweg 6
2628 XE – DELFT, The Netherlands

P: +31 15 27 88032

Visiting hours office
Monday, Tuesday, Thursday: 10:00 – 15:00


The ASCI office is located at the Delft University of Technology campus.  It is easily accessible by bicycle, public transport and car. The numbers of buildings can help you find your way around the campus. Make sure you remember the name and building number of your destination.

Contact us at +31 15 278 8032 or send us an email at

Symmetry-based learning from limited data

Symmetry-based learning from limited data

Author : Ivan Sosnovik
Promotor(s) : AW.M. Sneulders / Prof.dr. C.G.M. Snoek
University : University of Amsterdam
Year of publication : 2023
Link to repository : Link to thesis


In this thesis, we introduce new approaches for training better machine learning models for computer vision tasks in the absence of large labeled datasets. Our approach is based on equipping neural networks with the notion of symmetry for the sake of better learning real-world constraints without observing all their realizations in the training data. We start with explicit mathematical structures such as the scale group. We introduce Scale-Equivariant Steerable Networks, a class of convolutional neural networks that are equipped with an extra notion of scale variations. We present a theory and an effective implementation for these networks. Then we consider a wider group of non-affine transformations. And finally, we demonstrate that models can learn structures themselves by assuming symmetries in the input data.