[Lisa_seminaires] [Tea Talk] Maximilian Puelma Touzel (ENS Paris) Thur Mar 1 10:30AM AA1360

Michael Noukhovitch mnoukhov at gmail.com
Jeu 1 Mar 10:21:00 EST 2018


Reminder this is in 10 minutes!

On Mon, Feb 26, 2018, 22:35 Michael Noukhovitch <mnoukhov at gmail.com> wrote:

> This week we have *Maximilian Puelma Touzel *from* Ecole Normale
> Supérieure in Paris *giving a talk on *Thursday March 1* at *10:30AM *in
> room *AA1360*.
>
> **New* *If you'd like to meet with the presenter, choose which time slots
> work for you here (https://doodle.com/poll/2mxtkei7bnznht82) and we'll
> try to make it work!
>
> Guaranteed to be more fun than unboxing, come to the talk and be
> illuminated!
> Michael
>
> *TITLE *Don’t paint the box black: Using dynamical systems to understand
> the high-dimensional activity of cortex-inspired neural networks
>
> *KEYWORDS *biological NNs, learning dynamics, systems analysis,
> statistical physics
>
>
> *ABSTRACT*The dynamics of cortical circuits are thought to be responsible
> for much of the learning in higher vertebrates. Over the last decades, a
> data-driven theoretical effort in neuroscience has sought to understand the
> collective dynamics of 'task-ready' cortical activity. In this talk, I will
> first recount the work that led up to the first self-consistent mean-field
> theory of such activity in 2010. Employing a long-standing framework from
> dynamical systems and statistical physics suited for characterizing
> information processing in high-dimensional dynamics, subsequent work has
> focussed on understanding the properties of the underlying full spiking
> network dynamics. I will describe some of these approaches, and present
> original work that analytically treats the complex phase space geometry of
> a multi-stable regime exhibited by these models. The outlook for this
> general framework looks bright as we more broadly seek to elucidate
> high-dimensional learning dynamics in a variety of systems, both biological
> and machine.
>
> *BIO*
> Maximilian Puelma Touzel is a theoretical biophysicist interested in
> understanding how learning systems build and adapt representations of their
> environment. He studied math and physics at the University of Toronto and
> then theoretical neuroscience at the Max Planck Institute for Dynamics and
> Self-Organization in Göttingen, Germany, receiving a PhD there under the
> supervision of Fred Wolf. Currently, he is a post-doctoral fellow working
> on inference of probabilistic models of immune repertoire change with
> Aleksandra Walczak and Thierry Mora in the Laboratoire de Physique
> Théorique at the Ecole Normale Supérieure in Paris.
>
>
>
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