Publications associées à The physics of higher-order interactions in complex systems

Publications associées (45)

Towards an Understanding of Hydraulic Sensitivity: Graph Theory Contributions to Water Distribution Analysis

Water distribution systems (WDSs) are complex networks with numerous interconnected junctions and pipes. The robustness and reliability of these systems are critically dependent on their network structure, necessitating detailed analysis for proactive leak ...

MDPI2024

Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder

Ursula Röthlisberger, Martin Peter Bircher, Justin Villard

The accurate representation of the structural and dynamical properties of water is essential for simulating the unique behavior of this ubiquitous solvent. Here we assess the current status of describing liquid water using ab initio molecular dynamics, wit ...

Royal Soc Chemistry2024

Formation of the cavity on a planar interface subjected to a perturbed shock wave

Ho Ling Li, Naifu Peng

We report the mechanism and modeling for the formation of cavitylike structures on a planar interface subjected to a perturbed shock wave. The cavity is distinguished from bubbles and spikes formed in the standard Richtmyer-Meshkov instability (RMI). The t ...

AMER PHYSICAL SOC2023

Characterisation of electron cyclotron wall conditioning plasma in ASDEX Upgrade

Richard Pitts

Electron cyclotron wall condition (ECWC) discharges are characterised in ASDEX Upgrade with full tungsten plasma facing components and X2 polarised waves launched from the equatorial ports, relevant to ECWC conditions in ITER Pre-Fusion Power Operation pha ...

IOP Publishing Ltd2023

On the symmetries in the dynamics of wide two-layer neural networks

Lénaïc Chizat

We consider the idealized setting of gradient flow on the population risk for infinitely wide two-layer ReLU neural networks (without bias), and study the effect of symmetries on the learned parameters and predictors. We first describe a general class of s ...

AMER INST MATHEMATICAL SCIENCES-AIMS2023

Twisting instabilities in elastic ribbons with inhomogeneous pre-stress: A macroscopic analog of thermodynamic phase transition

Pedro Miguel Nunes Pereira de Almeida Reis, Michael Christopher Gomez

We study elastic ribbons subject to large, tensile pre-stress confined to a central region within the cross-section. These ribbons can buckle spontaneously to form helical shapes, featuring regions of alternating chirality (phases) that are separated by so ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Contrasting action and posture coding with hierarchical deep neural network models of proprioception

Alexander Mathis, Mackenzie Mathis, Matthias Bethge, Kai Jappe Sandbrink

Biological motor control is versatile, efficient, and depends on proprioceptive feedback. Muscles are flexible and undergo continuous changes, requiring distributed adaptive control mechanisms that continuously account for the body's state. The canonical r ...

eLIFE SCIENCES PUBL LTD2023

Data-driven approaches for non-invasive cuffless blood pressure monitoring

Clémentine Léa Aguet

Blood pressure (BP) is a crucial indicator of cardiovascular health. Hypertension is a common life-threatening condition and a key factor of cardiovascular diseases (CVDs). Identifying abnormal BP fluctuations can allow for early detection and management o ...

EPFL2023

Label-free plasmonic microarray for multiplexed analysis of cells and tumor organoids

Yen-Cheng Liu

Investigating the dynamic activities of protein expression and signaling in living organisms is a crucial focus of intense research aimed at elucidating the processes that underlie disease progression and improving treatments and drug development. Resolvin ...

EPFL2023

Network Alignment With Holistic Embeddings

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong, Thanh Trung Huynh

Network alignment is the task of identifying topologically and semantically similar nodes across (two) different networks. It plays an important role in various applications ranging from social network analysis to bioinformatic network interactions. Howeve ...

IEEE COMPUTER SOC2023

Hardware-Software co-design Methodologies for Edge AI Optimization

Flavio Ponzina

ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...

EPFL2023

A unified framework for Simplicial Kuramoto models

Alexis Arnaudon

Simplicial Kuramoto models have emerged as a diverse and intriguing class of models describing oscillators on simplices rather than nodes. In this paper, we present a unified framework to describe different variants of these models, categorized into three ...

2024

Privacy-Preserving Machine Learning on Graphs

Sina Sajadmanesh

Graph Neural Networks (GNNs) have emerged as a powerful tool for learning on graphs, demonstrating exceptional performance in various domains. However, as GNNs become increasingly popular, new challenges arise. One of the most pressing is the need to ensur ...

EPFL2023

Artificial Neural Network Training on an Optical Processor via Direct Feedback Alignment

Florent Gérard Krzakala

Artificial Neural Networks (ANN) are habitually trained via the back-propagation (BP) algorithm. This approach has been extremely successful: Current models like GPT-3 have O(10 11 ) parameters, are trained on O(10 11 ) words and produce awe-inspiring resu ...

IEEE2023

Equilibria in Network Constrained Energy Markets

Leonardo Massai

We study an energy market composed of producers who compete to supply energy to different markets and want to maximize their profits. The energy market is modeled by a graph representing a constrained power network where nodes represent the markets and lin ...

Elsevier2023

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity

Tilo Schwalger, Valentin Marc Schmutz

Bottom-up models of functionally relevant patterns of neural activity provide an explicit link between neuronal dynamics and computation. A prime example of functional activity patterns are propagating bursts of place-cell activities called hippocampal rep ...

PUBLIC LIBRARY SCIENCE2022

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Elisabetta Cornacchia

This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

EPFL2023

Studies on Types: Dormitories

Tiago André Pratas Borges, Anja Fröhlich, Estelle Lépine, Vanessa Pointet

Concepts of type and typology are not specific to architecture. Rather they represent an interdisciplinary approach to ordering knowledge and gaining insight. In the field of architecture, the study of types and typology offers a didactic perspective that ...

EPFL Press2022

Multi-fidelity regression using artificial neural networks: Efficient approximation of parameter-dependent output quantities

Jan Sickmann Hesthaven

Highly accurate numerical or physical experiments are often very time-consuming or expensive to obtain. When time or budget restrictions prohibit the generation of additional data, the amount of available samples may be too limited to provide satisfactory ...

ELSEVIER SCIENCE SA2022

Relative, local and global dimension in complex networks

Alexis Arnaudon

Dimension is a fundamental property of objects and the space in which they are embedded. Yet ideal notions of dimension, as in Euclidean spaces, do not always translate to physical spaces, which can be constrained by boundaries and distorted by inhomogenei ...

Nature Portfolio2022