Publications related to Small-world network

Large-scale brain network dynamics in very preterm children and relationship with socio-emotional outcomes: an exploratory study

Dimitri Nestor Alice Van De Ville, Vanessa Siffredi, Younes Farouj, Daniel Mourad Alfy Ramzy Tadros

Background Children born very preterm (VPT;

SPRINGERNATURE2022

A Topological characterisation of Weisfeiler-Leman equivalence classes

Graph Neural Networks (GNNs) are learning models aimed at processing graphs and signals on graphs. The most popular and successful GNNs are based on message passing schemes. Such schemes inherently have limited expressive power when it comes to distinguish ...

2022

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

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

The Role of Hub Neurons in Modulating Cortical Dynamics

Henry Markram, Oren Amsalem, Idan Segev, Eyal Gal, Michael London

Many neurodegenerative diseases are associated with the death of specific neuron types in particular brain regions. What makes the death of specific neuron types particularly harmful for the integrity and dynamics of the respective network is not well unde ...

2021

Atomic subgraphs and the statistical mechanics of networks

Sofia Charlotta Olhede

We develop random graph models where graphs are generated by connecting not only pairs of vertices by edges, but also larger subsets of vertices by copies of small atomic subgraphs of arbitrary topology. This allows for the generation of graphs with extens ...

2021

True scale-free networks hidden by finite size effects

Andrea Rinaldo, Samir Suweis, Amos Maritan

We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statisti ...

NATL ACAD SCIENCES2021

Validating atlas-based lesion disconnectomics in multiple sclerosis: A retrospective multi-centric study

Tobias Kober, Bénédicte Marie Maréchal, Reto Meuli, Jonas Richiardi, Mario Joao Fartaria de Oliveira

The translational potential of MR-based connectivity modelling is limited by the need for advanced diffusion imaging, which is not part of clinical protocols for many diseases. In addition, where diffusion data is available, brain connectivity analyses rel ...

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

Clinical connectome fingerprints of cognitive decline

Enrico Amico, Emahnuel Troisi Lopez

Brain connectome fingerprinting is rapidly rising as a novel influential field in brain network analysis. Yet, it is still unclear whether connectivity fingerprints could be effectively used for mapping and predicting disease progression from human brain d ...

2021

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Large-scale brain network dynamics in very preterm children and relationship with socio-emotional outcomes: an exploratory study

A Topological characterisation of Weisfeiler-Leman equivalence classes

Learning Bollobas-Riordan Graphs Under Partial Observability

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

The Role of Hub Neurons in Modulating Cortical Dynamics

Atomic subgraphs and the statistical mechanics of networks

True scale-free networks hidden by finite size effects

Validating atlas-based lesion disconnectomics in multiple sclerosis: A retrospective multi-centric study

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

Clinical connectome fingerprints of cognitive decline

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

Large-scale brain network dynamics in very preterm children and relationship with socio-emotional outcomes: an exploratory study

True scale-free networks hidden by finite size effects

Learning Bollobas-Riordan Graphs Under Partial Observability

A Topological characterisation of Weisfeiler-Leman equivalence classes

The Role of Hub Neurons in Modulating Cortical Dynamics

Atomic subgraphs and the statistical mechanics of networks

Validating atlas-based lesion disconnectomics in multiple sclerosis: A retrospective multi-centric study

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

Clinical connectome fingerprints of cognitive decline