World Wide relies on analytics signals to operate securely and keep research services available. Accept to continue, or leave the site.
Review the Privacy Policy for details about analytics processing.
Dr
CNRS & CEA Saclay
Showing your local timezone
Schedule
Tuesday, June 23, 2020
2:00 PM Europe/London
Seminar location
No geocoded details are available for this content yet.
Recording provided by the organiser.
Format
Recorded Seminar
Recording
Available
Host
The Neurotheory Forum
Seminar location
No geocoded details are available for this content yet.
The affinity between statistical physics and machine learning has long history, this is reflected even in the machine learning terminology that is in part adopted from physics. I will describe the main lines of this long-lasting friendship in the context of current theoretical challenges and open questions about deep learning. Theoretical physics often proceeds in terms of solvable synthetic models, I will describe the related line of work on solvable models of simple feed-forward neural networks. I will highlight a path forward to capture the subtle interplay between the structure of the data, the architecture of the network, and the learning algorithm.
Lenka Zdeborová
Dr
CNRS & CEA Saclay
neuro
neuro
The development of the iPS cell technology has revolutionized our ability to study development and diseases in defined in vitro cell culture systems. The talk will focus on Rett Syndrome and discuss t
neuro
Pluripotent cells, including embryonic stem (ES) and induced pluripotent stem (iPS) cells, are used to investigate the genetic and epigenetic underpinnings of human diseases such as Parkinson’s, Alzhe