I’m a machine learning researcher at Qualcomm and finishing my PhD in Machine Learning at the University of Amsterdam where I work with Max Welling. I received a BSc in CS from Utrecht University and a MSc in AI from the University of Amsterdam (both cum laude). In 2013, I cofounded Scyfer, a company specialized in deep active learning (acquired by Qualcomm in 2017). During summer 2015 I worked on unsupervised learning of equivariant representations with Geoff Hinton at Google DeepMind. During fall 2016 / spring 2017 I spent some time at OpenAI. I received the 2017 Google PhD Fellowship. Here is my CV.
My research is focussed on learning of equivariant representations for data-efficient deep learning. Besides improving data-efficiency, “equivariance to symmetry transformations” provides one of the first rational design principles for deep neural networks, and allows them to be more easily interpreted in geometrical terms than ordinary black-box networks.
I’m very excited by the application of these methods to medical image analysis, where data-efficiency is critical. More broadly, I’m fascinated by all things related to human cognition and perception, pure mathematics, and theoretical physics.
T.S. Cohen, M. Geiger, J. Koehler, M. Welling, Spherical CNNs. ICLR 2018 (oral presentation).
E. Hoogeboom, J.W.T. Peters, T.S. Cohen, M. Welling, HexaConv. ICLR 2018.
T.S. Cohen, M. Geiger, J. Koehler, M. Welling, Convolutional Networks for Spherical Signals. In Principled Approaches to Deep Learning Workshop ICML 2017.
A. Eck, L.M. Zintgraf, E.F.J. de Groot, T.G.J. de Meij, T.S. Cohen, P.H.M. Savelkoul, M. Welling, A.E. Budding, Interpretation of microbiota-based diagnostics by explaining individual classifier decisions, BMC Bioinformatics, 2017.
T. Matiisen, A. Oliver, T.S. Cohen, J. Schulman, Teacher-Student Curriculum Learning. Deep Reinforcement Learning Symposium, NIPS 2017
T.S. Cohen, M. Welling, Steerable CNNs. International Conference on Learning Representations (ICLR), 2017
L.M. Zintgraf, T.S. Cohen, T. Adel, M. Welling, Visualizing Deep Neural Network Decisions: Prediction Difference Analysis. International Conference on Learning Representations (ICLR), 2017
T. Adel, T.S. Cohen, M. Caan, M. Welling, 3D Scattering Transforms for Disease Classification in Neuroimaging. Neuroimage: clinical, 2017 (accepted)
L.M. Zintgraf, T.S. Cohen, M. Welling, A New Method to Visualize Deep Neural Networks. ArXiv preprint 1603.02518, 2016
T.S. Cohen, M. Welling, Transformation Properties of Learned Visual Representations. International Conference on Learning Representations (ICLR), 2015.
T.S. Cohen, Learning Transformation Groups and their Invariants. Master’s thesis, University of Amsterdam, 2013. (1st place University of Amsterdam thesis prize 2014)