activity
20242026
most citedFibration symmetry-breaking supports functional transitions in a brain network engaged in language

1 citations · 2 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Emergence of Fibrations, Compression, and Symmetry Breaking in Artificial Neural Networks

Osvaldo M Velarde, Lucas C Parra, Alireza Hashemi +1

Artificial neural networks are often regarded as powerful yet opaque black boxes. Here, we demonstrate that learning in deep neural networks generates local symmetries known in gra…

q-bio.MN2025

Symmetries of Living Systems: Symmetry Fibrations and Synchronization in Biological Networks

Hernan A. Makse, Paolo Boldi, Francesco Sorrentino +1

A symmetry is a `change without change'. As simple as it sounds, this concept is the fundamental cornerstone that unifies all branches of theoretical physics. Virtually all physica…

nlin.AO2025

Extreme vulnerability to intruder attacks destabilizes network dynamics

Amirhossein Nazerian, Sahand Tangerami, Malbor Asllani +3

Consensus, synchronization, formation control, and power grid balance are examples of desirable dynamical states that arise in networks. Here we investigate how such states can be…

q-bio.NC2024

Symmetries and synchronization from whole-neural activity in {\it C. elegans} connectome: Integration of functional and structural networks

Bryant Avila, Pedro Augusto, David Phillips +3

Understanding the dynamical behavior of complex systems from their underlying network architectures is a long-standing question in complexity theory. Therefore, many metrics have b…

q-bio.NC2024★ 1 cited

Fibration symmetry-breaking supports functional transitions in a brain network engaged in language

Tommaso Gili, Bryant Avila, Luca Pasquini +7

In his book 'A Beautiful Question', physicist Frank Wilczek argues that symmetry is 'nature's deep design,' governing the behavior of the universe, from the smallest particles to t…

cs.LG2024★ 1 cited

The Role of Fibration Symmetries in Geometric Deep Learning

Osvaldo Velarde, Lucas Parra, Paolo Boldi +1

Geometric Deep Learning (GDL) unifies a broad class of machine learning techniques from the perspectives of symmetries, offering a framework for introducing problem-specific induct…