Jörn-Henrik Jacobsen


I am a Ph.D. student at the University of Amsterdam at the crossroads between deep learning, computer vision, and neuroscience, supervised by Prof. Arnold Smeulders. My background is in physics with a specialization in neuroscience.

My current research is focused on the problem that we have little knowledge about why Deep Networks perform so well and which properties of the data they use to solve given tasks. We are working on understanding and improving Deep Convolutional Networks through imposing additional structure on them. Carefully structured models can help us to open up the "black-box", so we can draw actual conclusions about what these networks learn, how they learn and when they will fail.
Our most recent effort into this direction is a collaboration with Stéphane Mallat and Edouard Oyallon. This joint work is focused on "Multiscale Hierarchical CNNs", a framework for CNNs whose properties can be mathematically and semantically understood.

I will finish my Ph.D. by the end of 2017 and am currently looking for exciting research positions.


J.-H. Jacobsen, B. de Brabandere, A.W.M. Smeulders. Dynamic Steerable Blocks in Deep Residual Networks. BMVC, 2017. [Paper]

J.-H. Jacobsen, E. Oyallon, S. Mallat, A.W.M. Smeulders. Multiscale Hierarchichal Convolutional Networks. Under Submission, 2017. [Paper, Code]

J.-H. Jacobsen, B. de Brabandere, A.W.M. Smeulders. Dynamic Steerable Frame Networks. Pre-print, 2017. [Paper]

J.-H. Jacobsen, J. v. Gemert, Z. Lou, A.W.M. Smeulders. Structured Receptive Fields in CNNs. CVPR, 2016. [Paper, Code]

J.-H. Jacobsen, A.W.M. Smeulders. Deep Learning for Neuroimage Classification. OHBM, 2015.

J.-H. Jacobsen, J. Stelzer, T. H. Fritz, G. Chételat, R. L. Joie, R. Turner. Why musical memory can be preserved in advanced Alzheimer's disease. Brain, 2015. [Paper].

See also: Scientific commentary by Clark and Warren; Science News; Reddit Frontpage; SciFeeds; MedicalXpress; Max-Planck-Society

R. Turner, J.-H. Jacobsen. What stays when everything goes. OUPblog, 2015. Oxford University Press Blog.


Hierarchical CNNs - Edouard Oyallon and Stéphane Mallat; Data Team, ENS, Paris.

Dynamic Steerable Frame Networks - Bert de Brabandere; ESAT, KU Leuven.

Large-scale fMRI Brain analysis - Max-Planck-Institute CBS, Leipzig; Max-Planck-Institute Kyb, Tübingen.

Alzheimer's and Musical Memory Preservation - Prof. Robert Turner; Max-Planck-Institute CBS, Leipzig.

Structured Receptive Field CNNs - Jan v. Gemert, TU Delft.


Jörn-Henrik Jacobsen
Informatics Institute
University of Amsterdam
Science Park 904
1098 XH Amsterdam
The Netherlands
Email: j.jacobsen@uva.nl