A team of scientists from TU Berlin, Fraunhofer Heinrich Hertz Institute (HHI) and University of Oslo has jointly received the 2020 “Pattern Recognition Best Paper Award” and “Pattern Recognition Medal” of the international scientific journal Pattern Recognition. The award committee honored the publication “Explaining Nonlinear Classification Decisions with Deep Taylor Decomposition” by Dr. Grégoire Montavon and Prof. Dr. Klaus-Robert Müller from TU Berlin, Prof. Dr. Alexander Binder from University of Oslo, as well as Dr. Wojciech Samek and Dr. Sebastian Lapuschkin from HHI.
The publication addresses the so-called black box problem. Machine Learning methods, in particular Deep Learning, successfully solve a variety of tasks. However, in most cases they fail to provide the information that has led to a particular decision. The paper tackles this problem by using a pixel-by-pixel decomposition of nonlinear classifications and evaluates the procedure in different scenarios. This method provides a theoretical framework for Explainable Artificial Intelligence (XAI) that is generally applicable. XAI is a major research field of the Berlin Institute for the Foundations of Learning and Data (BIFOLD), of which the authors from TU Berlin and HHI are members.
The award was presented to Grégoire Montavon in January 2021, during the virtual International Conference on Pattern Recognition (ICPR). The “Pattern Recognition Best Paper Award” is granted every two years. It recognizes a highly cited paper in the area of pattern recognition and its application areas such as image processing, computer vision and biometrics.
“We are very proud to receive this award and for our work to be highlighted within the global scientific community.”
Dr. Grégoire Montavon.