Publication

A Measure of Dynamical Efficiency for Multimodal Interconnected Urban Systems

Publications associées (26)

Benign Overfitting in Deep Neural Networks under Lazy Training

Volkan Cevher, Zhenyu Zhu, Grigorios Chrysos, Fanghui Liu

This paper focuses on over-parameterized deep neural networks (DNNs) with ReLU activation functions and proves that when the data distribution is well-separated, DNNs can achieve Bayesoptimal test error for classification while obtaining (nearly) zero-trai ...

2023

ReLU Neural Network Galerkin BEM

Fernando José Henriquez Barraza

We introduce Neural Network (NN for short) approximation architectures for the numerical solution of Boundary Integral Equations (BIEs for short). We exemplify the proposed NN approach for the boundary reduction of the potential problem in two spatial dime ...

SPRINGER/PLENUM PUBLISHERS2023

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-constrained Cycles

Paolo Ienne, Kubilay Atasu, Jovan Blanusa

Cycles are one of the fundamental subgraph patterns and being able to enumerate them in graphs enables important applications in a wide variety of fields, including finance, biology, chemistry, and network science. However, to enable cycle enumeration in r ...

Assoc Computing Machinery2023

Diffusion of energy technologies: the role and dynamics of supply-side information networks

Claudia Rebeca Binder Signer, Romano Tobias Wyss, Gloria Serra Coch, Maria Anna Hecher

The diffusion of energy technologies is key for supporting the energy transition. While social influence and peer effects have been extensively studied on the demand side and found to impact adoption, less focus has been given to the role of information ne ...

2023

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-Constrained Cycles

Paolo Ienne, Kubilay Atasu, Jovan Blanusa

Finding cycles in directed graphs enables important applications in various domains such as finance, biology, chemistry, and network science. However, as the size of graph datasets continues to grow, it becomes increasingly difficult to discover cycles wit ...

arXiv2023

Localizing Traffic Differentiation

Aikaterini Argyraki, Pavlos Nikolopoulos, Zeinab Shmeis, Muhammad Abdullah

Network neutrality is important for users, content providers, policymakers, and regulators interested in understanding how network providers differentiate performance. When determining whether a network differentiates against certain traffic, it is importa ...

2023