NEWS
Explainable AI illuminates the course of history
Understanding the evolution and dissemination of human knowledge over time is a long-cherished dream of many historians. A dream that faced many challenges due to the abundance of historical materials and limited specialist resources. However, the digitization of many historical archives presents new opportunities for AI-supported analysis.
AI in medicine: new approach for more efficient diagnostics
Researchers from LMU, BIFOLD, and Charité have developed a new AI tool that uses imaging data to also detect less frequent diseases of the gastrointestinal tract. In contrast to conventional models, the new AI only needs training data from common findings to detect deviations.
EVENTS
Lunch Talk: Philipp Wiesner „Exploring the Trade-Off Between Carbon Footprint and User Experience of ML Inference Services“
Philipp Wiesner will present insights into his research on "Exploring the Trade-Off Between Carbon Footprint and User Experience of ML Inference Services".
AI Future Forum
Artificial intelligence is more than just a technological trend; it is a fundamental building block for the future of our economy. Thanks to Berlin's unique start-up community, innovative SMEs, numerous tech talents and cutting-edge research, one thing is clear: Berlin can do AI! On November 6th, Berlin will discuss what has already happened in the field of AI in the capital and what still needs to happen.
Our Mission
BIFOLD conducts groundbreaking foundational research in Big Data Management (DM) and Machine Learning (ML), as well as their intersection, to educate the talents of the future and to create high-impact knowledge.
OPPORTUNITIES
BIFOLD welcomes job applications from interested parties year-round.
PUBLICATIONS
Robert A. Vandermeulen, Wai Ming Tai, Bryon Aragam
Breaking the curse of dimensionality in structured density estimation
Dilyara Bareeva, Galip Ümit Yolcu, Anna Hedström, Niklas Schmolenski, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
Quanda: An Interpretability Toolkit for Training Data Attribution Evaluation and Beyond
Adil Kabylda, J. Thorben Frank, Sergio Suarez Dou, Almaz Khabibrakhmanov, Leonardo Medrano Sandonas, Oliver T. Unke, Stefan Chmiela, Klaus-Robert Müller, Alexandre Tkatchenko
Molecular Simulations with a Pretrained Neural Network and Universal Pairwise Force Fields
GRADUATE SCHOOL
Based on a highly competitive application process, the BIFOLD Graduate School offers an innovative fast-track PhD Program for students holding a bachelor’s degree, as well as a PhD Program for students with a master’s degree.
INSTITUTIONAL PARTNERS
ASSOCIATED PARTNERS
