Bridging scales: At the crossroads among renormalisation group, multi-scale modelling, and deep learning

Machine learning will define the 21st Century: from simple image classification to text generation and decision making, its impact on society will be nothing but immense. At present, the detailed mechanisms behind the power of AI still evade our understanding; growing evidence, however, suggests that it is possible to rationalise how deep learning works in terms that are very familiar to theoretical physicists, that is, the renormalisation group. The systematic, hierarchical coarsening of detailed information into increasingly simpler and more collective features is a cornerstone of modern physics, and it can be leveraged not only to make sense of machine learning’s baffling capabilities, but also and most importantly to steer its development. This workshop will explore the area where theoretical physics of soft and condensed matter and deep learning overlap, looking for novel and more powerful tools to model, investigate, and understand the world around us.

EMMI logo

Emmi supported workshop (www.gsi.de/emmi)

Organizers

  • Roberto Menichetti (University of Trento and INFN-TIFPA)
  • Francesco Pederiva (University of Trento and INFN-TIFPA)
  • Raffaello Potestio (University of Trento and INFN-TIFPA)
  • Alessandro Roggero (University of Trento and INFN-TIFPA)

Contacts

See complete details and information

Registration

Register

Registration available until 22/03/2024.

Privacy Notice

Pursuant to art. 13 of EU Regulation No. 2016/679 – General Data Protection Regulation and as detailed in the Privacy Policy for FBK-ECT* event’s participants, we inform you that the event will be recorded and disclosed on the FBK-ECT* institutional channels. In order not to be filmed or recorded, you can disable the webcam and/or mute the microphone during virtual events or inform the FBK-ECT* staff who organize the public event beforehand.
WordPress Cookie Notice by Real Cookie Banner