Papers We Love #7: CNNs & Francisco Varela

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Papers We Love is back with two talks!

We start at 7pm with socializing, some drinks and food provided by INNOQ.

The first talk will be about Group Equivariant Convolutional and Capsule Networks by Tolga Birdal.

The second talk will be about the Mathematical Work of Francisco Varela by Johannes Drever.


Group Equivariant Convolutional and Capsule Networks

Convolutional neural networks (CNN) have demonstrated tremendous capabilities paving the way for the AI revolution. Part of this is due to their translational invariance, or in a more general terminology, equivariance. While for typical CNN, shift of the input images were handled at no additional effort, dealing with rotational changes was a nuisance. This is because CNNs, as well as many other state of the art learning machinery, are not capable of handling transformations other than translations, by design. Luckily, many transformations that are to be taken care of are elements of what is called a mathematical group. With this notion, Cohen and Welling have re-addressed the conventional CNNs devising G-CNN, the group equivariant convolutional networks. Given the proper definition and constructs of a group, such as the special orthogonal group of rotations, G-CNN achieve equivariant or invariant features to the group actions, such as rotating an input image. This achieved by what is called a G-Conv, the group convolution. Lenssen et al. have then taken this idea further developing the Group Equivariant Capsule Networks, an extension of the group-equivariance properties to the famous capsule networks. In this talk, we are primarily interested in the latter, drawing the necessary background from the formers. Tolga's purpose is to introduce, motivate, discuss and brainstorm on these state of the art advancements.

Tolga Birdal has recently defended his PhD thesis at the Computer Vision Group, Chair for Computer Aided Medical Procedures, Technical University of Munich and was a Doktorand at Siemens AG. He completed his Bachelors as an Electronics Engineer at the Sabanci University in 2008. In his subsequent postgraduate programme, he studied Computational Science and Engineering at Technical University of Munich. In continuation to his Master's thesis on "3D Deformable Surface Recovery Using RGBD Cameras", he now focuses his research and development on large object detection, pose estimation and reconstruction using point clouds. Recently, he is awarded both Ernst von Siemens Scholarship and EMVA Young Professional Award 2016 for his PhD work. He has several publications at the well respected venues such as NIPS, CVPR, ICCV, ECCV, IROS, ICASSP and 3DV. Aside from his academic life, Tolga is a natural Entrepreneur. He has co-founded multiple companies including Befunky, a widely used web based image processing platform. For further information, visit and


Mathematical Work of Francisco Varela

Epistemology is the study of the nature of knowledge, justification, and the rationality of belief. Second order cybernetics is a specific epistemology which takes a unified view on biological systems and machines. Francisco Varela is one of the most influential thinkers in this area. He has contributed to the development the concept of autopeiesis. In this this talk an introduction to the ideas of second order cybernetics will be given.

Johannes Drever has studied computer science at the TUM with a focus on machine learning and did a PhD at the department of neurology at the LMU. He works as a software developer at Linova on applications in the aviation, health and torsional vibration industry. He is a Haskell enthusiast and has a growing interest in applied category theory.