BIFOLD

Berlin Institute for the Foundations of Learning and Data

Duration: July 2018 – present

BIFOLD research groups conduct fundamental research on a wide range of topics concerning foundations and methods of Artificial Intelligence (AI). This includes the management and processing of distributed and Big Data. As Machine Learning (ML) is one of the main fields for modern AI and the new wave of AI applications, we also focus on a variety of Machine Learning methods such as reinforced and Bayesian Machine Learning as well as unsupervised and recurrent Deep Learning.

Project partners:

TU Berlin, HU Berlin, FU Berlin, Charité, Uni Potsdam, Uni Braunschweig, Fraunhofer FOKUS, DFKI, Zuse Institute, WIAS, MDC, HPI, MPI

Publications:

L. Ruff, J. R. Kauffmann, R. A. Vandermeulen, G. Montavon, W. Samek, M. Kloft, T. G. Dietterich, K.-R. Müller. A Unifying Review of Deep and Shallow Anomaly Detection. Proceedings of the IEEE, 2021.