Publications related to Network science

Optimal routing and design of CO2 based district anergy networks

One of the main global goals is the reduction of the energy consumption and the most appropriate way for achieving this aim is to target one of most critical sectors, the residential. The selected technology for this work is the district energy network, wh ...

2022

The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment

Enrico Amico, Antonella Romano

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to ...

ELSEVIER SCI LTD2022

Face Reconstruction Fromdeep Facial Embeddings Using A Convolutional Neural Network

Sébastien Marcel, Hatef Otroshi Shahreza

State-of-the-art (SOTA) face recognition systems generally use deep convolutional neural networks (CNNs) to extract deep features, called embeddings, from face images. The face embeddings are stored in the system's database and are used for recognition of ...

IEEE2022

Physics-informed neural networks for diffraction tomography

Demetri Psaltis, Carlo Gigli, Amirhossein Saba Shirvan, Ahmed Ayoub

We propose a physics-informed neural network (PINN) as the forward model for tomographic reconstructions of biological samples. We demonstrate that by training this network with the Helmholtz equation as a physical loss, we can predict the scattered field ...

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS2022

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

Cluster-and-Conquer: When Randomness Meets Graph Locality

Anne-Marie Kermarrec, Olivier Ruas

K-Nearest-Neighbors (KNN) graphs are central to many emblematic data mining and machine-learning applications. Some of the most efficient KNN graph algorithms are incremental and local: they start from a random graph, which they incrementally improve by tr ...

IEEE COMPUTER SOC2021

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

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

Facilitators First: Building a Tool With Facilitators to Foster a More Collaborative Makerspace Community Through Movement Traces

Bertrand Roland Schneider, Léonore Valentine Guillain

Research indicates that makerspaces equip students with the practical skills needed to build their own projects and thrive in the twenty-first-century workforce. While the appeal of makerspaces lies in their spirit of tinkering and community-driven ethos, ...

ASSOC COMPUTING MACHINERY2021

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

Dimitri Nestor Alice Van De Ville, Maude Schneider, Daniela Maria Zöller, Anjali Bagunu Tarun

Causal interactions between specific psychiatric symptoms could contribute to the heterogenous clinical trajectories observed in early psychopathology. Current diagnostic approaches merge clinical manifestations that co-occur across subjects and could sign ...

eLIFE SCIENCES PUBL LTD2021

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Optimal routing and design of CO2 based district anergy networks

The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment

Face Reconstruction Fromdeep Facial Embeddings Using A Convolutional Neural Network

Physics-informed neural networks for diffraction tomography

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

Cluster-and-Conquer: When Randomness Meets Graph Locality

True scale-free networks hidden by finite size effects

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

Facilitators First: Building a Tool With Facilitators to Foster a More Collaborative Makerspace Community Through Movement Traces

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

Physics-informed neural networks for diffraction tomography

True scale-free networks hidden by finite size effects

Cluster-and-Conquer: When Randomness Meets Graph Locality

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

Facilitators First: Building a Tool With Facilitators to Foster a More Collaborative Makerspace Community Through Movement Traces

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

Optimal routing and design of CO2 based district anergy networks

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

The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment

Face Reconstruction Fromdeep Facial Embeddings Using A Convolutional Neural Network