
Mayalen Etcheverry
@mayalen_etc
Working on AI for automated discovery in science @Syensqo @CNRS
ID: 1148131709428424704
http://mayalenetcheverry.com 08-07-2019 07:28:25
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Symbolic dynamics bridges from #DynamicalSystems to computation/ #AI! In our #NeurIPS2024 (NeurIPS Conference) paper we present a new network architecture, Almost-Linear RNNs, that finds most parsimonious piecewise-linear representations of DS from data: arxiv.org/abs/2410.14240 1/4





Everything you love about generative models — now powered by real physics! Announcing the Genesis project — after a 24-month large-scale research collaboration involving over 20 research labs — a generative physics engine able to generate 4D dynamical worlds powered by a physics


The version of record is out in eLife - the journal - elifesciences.org/articles/92683 - the hard work of Mayalen Etcheverry , @Clement_MF_ , Pierre-Yves Oudeyer as we try to develop tools to characterize the behavior space of gene-regulatory networks (and pathways more broadly). For the interactive version of

Can we study gene regulatory networks from a behavioralist perspective, as "agents" navigating in transcriptional space? Our new paper at eLife - the journal explores this approach combining Michael Levin 's vision on basal cognition with Inria Flowers team 's automated discovery algorithms.



We're excited to announce the first Evolving Self-organisation workshop at GECCO 2025! Submission deadline: March 26, 2025 More information: …-self-organisation-workshop.github.io

What Is Life? Evolution as Computation By Blaise Agüera (@blaiseaguera.bsky.social) Just finished reading this thought-provoking little book. Highly recommended if you’re interested in artificial life, self-replicating computer code, how it all relates to evolution, chaos, and AI. mitpress.mit.edu/9780262554091/…



i just got an art grant from the council for the arts at MIT! *Tangible Dreams* will let visitors experiment and play with a physical neural network generating images real-time—by twisting knobs and switches, by reconnecting nodes together Arts at MIT




