Publication

Resilience To Contagion In Financial Networks

Publications associées (28)

Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

Danilo Saccani, Melanie Nicole Zeilinger

In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met. Drawing our motivation from ...

IEEE2023

Community-based reconstruction and simulation of a full-scale model of region CA1 of rat hippocampus

Henry Markram, Eilif Benjamin Muller, Srikanth Ramaswamy, Michael Reimann, James Gonzalo King, Lida Kanari, Ying Shi, Armando Romani, Davide Bella, Felix Schürmann

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, i ...

2024

Predicting nonlinear optical scattering with physics-driven neural networks

Demetri Psaltis, Carlo Gigli, Ahmed Ayoub

Deep neural networks trained on physical losses are emerging as promising surrogates for nonlinear numerical solvers. These tools can predict solutions to Maxwell's equations and compute gradients of output fields with respect to the material and geometric ...

AIP Publishing2023

Metallicity Distribution Functions of 13 Ultra-faint Dwarf Galaxy Candidates from Hubble Space Telescope Narrowband Imaging

Nicolas Lawrence Etienne Longeard

We present uniformly measured stellar metallicities of 463 stars in 13 Milky Way (MW) ultra-faint dwarf galaxies (UFDs; M-V = -7.1 to -0.8) using narrowband CaHK (F395N) imaging taken with the Hubble Space Telescope. This represents the largest homogeneous ...

Iop Publishing Ltd2023

Worst-Case Delay Analysis of Time-Sensitive Networks with Network Calculus

Seyed Mohammadhossein Tabatabaee

Time-sensitive networks, as in the context of IEEE Time-Sensitive Networking (TSN) and IETF Deterministic Networking (DetNet), offer deterministic services with guaranteed bounded latency in order to support safety-critical applications. In this thesis, we ...

EPFL2023

Rapid Network Adaptation: Learning to Adapt Neural Networks Using Test-Time Feedback

Amir Roshan Zamir, Oguzhan Fatih Kar, Shuqing Teresa Yeo, Zahra Sodagar

We propose a method for adapting neural networks to distribution shifts at test-time. In contrast to training-time robustness mechanisms that attempt to anticipate and counter the shift, we create a closed-loop system and make use of test-time feedback sig ...

Ieee Computer Soc2023

Single fraction and hypofractionated radiosurgery for perioptic meningiomas-tumor control and visual outcomes: a systematic review and meta-analysis

Constantin Tuleasca

Perioptic meningiomas, defined as those that are less than 3 mm from the optic apparatus, are challenging to treat with stereotactic radiosurgery (SRS). Tumor control must be weighed against the risk of radiation-induced optic neuropathy (RION), as both tu ...

Springer2023

The kinectome: A comprehensive kinematic map of human motion in health and disease

Enrico Amico, Antonella Romano, Emahnuel Troisi Lopez

Human voluntary movement stems from the coordinated activations in space and time of many musculoskeletal segments. However, the current methodological approaches to study human movement are still limited to the evaluation of the synergies among a few body ...

WILEY2022

An automatized signal timing detection at signalized intersections with detailed vehicle trajectory data

Nikolaos Geroliminis, Emmanouil Barmpounakis, Jasso Espadaler Clapés

Signalized intersections are a fundamental part of urban networks. Their understanding is crucial to identify congestion patterns, queues, delays, and safety issues in local and network level. In this work, we analyze multimodal vehicle trajectories and pr ...

2022

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