I study Deep Neural Networks for Computer Vision, like CNNs and Vision Transformers, and how they learn to do their job. Topics of choice include learned equivariance, position information and the inductive bias of the self-attention operation. I’ve also dabbled in implicit neural convolutional operators a bit.
paper with colleagues at TU Delft.Co-authored
paper with BSc students at TU Delft.Co-authored
I was head TA and lecturer in the 2023 edition of CV by Deep Learning at TU Delft.
We provide a high bandwidth, alias-free convolutional kernel parameterization with learnable kernel size and constant parameter cost.
I am always willing to talk about collaboration or supervision. Please find my contact info at the top of the page.
TU Delft, building 28, room 6.E.280
Van Mourik Broekmanweg 6
2628 XE Delft