Publications related to An affected core drives network integration deficits of the structural connectome in 22q11.2 deletion syndrome

Estimating the Topology of Preferential Attachment Graphs Under Partial Observability

This work addresses the problem of learning the topology of a network from the signals emitted by the network nodes. These signals are generated over time through a linear diffusion process, where neighboring nodes exchange messages according to the underl ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Investigating cognitive ability using action-based models of structural brain networks

Enrico Amico

Recent developments in network neuroscience have highlighted the importance of developing techniques for analysing and modelling brain networks. A particularly powerful approach for studying complex neural systems is to formulate generative models that use ...

OXFORD UNIV PRESS2022

The structural connectome and motor recovery after stroke: predicting natural recovery

Jean-Philippe Thiran, Friedhelm Christoph Hummel, Gabriel Girard, Takuya Morishita, Elena Beanato, Maximilian Jonas Wessel, Chang-Hyun Park, Philipp Johannes Koch, Philip Egger, Giorgia Giulia Evangelista

Stroke patients vary considerably in terms of outcomes: some patients present ‘natural’ recovery proportional to their initial impairment (fitters), while others do not (non-fitters). Thus, a key challenge in stroke rehabilitation is to identify individual ...

2021

NICEpath: Finding metabolic pathways in large networks through atom-conserving substrate-product pairs

Vassily Hatzimanikatis, Jasmin Maria Hafner

Motivation: Finding biosynthetic pathways is essential for metabolic engineering of organisms to produce chemicals, biodegradation prediction of pollutants and drugs, and for the elucidation of bioproduction pathways of secondary metabolites. A key step in ...

OXFORD UNIV PRESS2021

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Wulfram Gerstner, Clément Hongler, Johanni Michael Brea, Francesco Spadaro, Berfin Simsek, Arthur Jacot

We study how permutation symmetries in overparameterized multi-layer neural networks generate `symmetry-induced' critical points. Assuming a network with

L

layers of minimal widths

r_1^*, \ldots, r_{L-1}^*

reaches a zero-loss minimum at $ r_1^*! \c ...

2021

Learning Bollobas-Riordan Graphs Under Partial Observability

Ali H. Sayed, Michele Cirillo

This work examines the problem of learning the topology of a network (graph learning) from the signals produced at a subset of the network nodes (partial observability). This challenging problem was recently tackled assuming that the topology is drawn acco ...

IEEE2021

Local Tomography of Large Networks Under the Low-Observability Regime

Ali H. Sayed, Augusto José Rabelo Almeida Santos

This article studies the problem of reconstructing the topology of a network of interacting agents via observations of the state-evolution of the agents. We focus on the large-scale network setting with the additional constraint of partial observations, wh ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Systematic model reduction captures the dynamics of extrinsic noise in biochemical subnetworks

Barbara Bravi

We consider the general problem of describing the dynamics of subnetworks of larger biochemical reaction networks, e.g., protein interaction networks involving complex formation and dissociation reactions. We propose the use of model reduction strategies t ...

AMER INST PHYSICS2020

Simplicity in complex networks: a path-based centrality

Nikolaos Geroliminis, Leonardo Bellocchi

Understanding travel behaviour in transportation system is key challenge to calibrate and simulate the usage of urban mobility networks. We define in this work a path-based centrality based on the simplicity of the path between two locations in road networ ...

2020

A brief exposure to rightward prismatic adaptation changes resting-state network characteristics of the ventral attentional system

Patric Hagmann, Stephanie Clarke

A brief session of rightward prismatic adaptation (R-PA) has been shown to alleviate neglect symptoms in patients with right hemispheric damage, very likely by switching hemispheric dominance of the ventral attentional network (VAN) from the right to the l ...

2020

An affected core drives network integration deficits of the structural connectome in 22q11.2 deletion syndrome

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Estimating the Topology of Preferential Attachment Graphs Under Partial Observability

Investigating cognitive ability using action-based models of structural brain networks

The structural connectome and motor recovery after stroke: predicting natural recovery

NICEpath: Finding metabolic pathways in large networks through atom-conserving substrate-product pairs

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Learning Bollobas-Riordan Graphs Under Partial Observability

Local Tomography of Large Networks Under the Low-Observability Regime

Systematic model reduction captures the dynamics of extrinsic noise in biochemical subnetworks

Simplicity in complex networks: a path-based centrality

A brief exposure to rightward prismatic adaptation changes resting-state network characteristics of the ventral attentional system

Estimating the Topology of Preferential Attachment Graphs Under Partial Observability

NICEpath: Finding metabolic pathways in large networks through atom-conserving substrate-product pairs

Investigating cognitive ability using action-based models of structural brain networks

Systematic model reduction captures the dynamics of extrinsic noise in biochemical subnetworks

A brief exposure to rightward prismatic adaptation changes resting-state network characteristics of the ventral attentional system

Local Tomography of Large Networks Under the Low-Observability Regime

Learning Bollobas-Riordan Graphs Under Partial Observability

Simplicity in complex networks: a path-based centrality

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

The structural connectome and motor recovery after stroke: predicting natural recovery