David Nordström
PhD Student in Deep Learning
I like Deep Learning and Computer Vision. Make GPUs go brrr.
Publications
Stronger ViTs With Octic Equivariance
David Nordström, Johan Edstedt, Fredrik Kahl, Georg Bökman
Introducing octic-equivariant Vision Transformers, achieving 40% FLOPs reduction while improving both classification and segmentation performance for DeiT III and DINOv2.
Flopping for FLOPs: Leveraging equivariance for computational efficiency
Georg Bökman, David Nordström, Fredrik Kahl
We show that building flopping-equivariance into modern vision architectures reduces the number of FLOPs and increases performance.
Education
PhD in Geometric Deep Learning
Chalmers University of Technology
Research focus on equivariant neural networks and efficient deep learning architectures.
M.Sc. in Engineering Mathematics
Chalmers University of Technology
International Experience
Exchange Semester at UC Berkeley
Exchange Semester at Seoul National University
B.Sc. in Industrial Engineering
Chalmers University of Technology
B.Sc. in Economics
University of Gothenburg
Completed in parallel with Industrial Engineering degree
Get in Touch
I'm always open to research collaborations and discussions.
I'm always open to research collaborations and discussions.