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A method of calculating path observation likelihood from GPS data

Publications associées (37)

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DeepNC: Deep Generative Network Completion

Andreas Oliver Spitz

Most network data are collected from partially observable networks with both missing nodes and missing edges, for example, due to limited resources and privacy settings specified by users on social media. Thus, it stands to reason that inferring the missin ...

IEEE COMPUTER SOC2022

Social Learning Under Inferential Attacks

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon, Konstantinos Ntemos

A common assumption in the social learning literature is that agents exchange information in an unselfish manner. In this work, we consider the scenario where a subset of agents aims at driving the network beliefs to the wrong hypothesis. The adversaries a ...

IEEE2021

Dynamic Quantification of the Effect of Traffic Congestion on a Multilayer Network

The paper “Dynamic efficiency in multilayer transportation networks” (Bellocchi, Geroliminis, 2018) [1] introduced new performance measures to quantify dynamically the effect of traffic congestion in a multilayer network. Based on these measures, we explor ...

2020

Extrapolating Paths with Graph Neural Networks

Andreas Loukas, Jean-Baptiste Francis Marie Juliette Cordonnier

We consider the problem of path inference: given a path prefix, i.e., a partially observed sequence of nodes in a graph, we want to predict which nodes are in the missing suffix. In particular, we focus on natural paths occurring as a by-product of the int ...

IJCAI, Inc.2019

Alignment and Assembly

Lyudmila Yartseva

Over recent years, many large network datasets become available, giving rise to novel and valuable applications of data mining and machine learning techniques. These datasets include social networks, the structure of the Internet, and protein-interaction n ...

EPFL2017

Network Alignment: Theory, Algorithms, and Applications

Ehsan Kazemi

Networks are central in the modeling and analysis of many large-scale human and technical systems, and they have applications in diverse fields such as computer science, biology, social sciences, and economics. Recently, network mining has been an active a ...

EPFL2016

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

Alessandra Griffa, Patric Hagmann, Marie Schaer, Frantisek Vasa

Chromosome 22q11.2 deletion syndrome (22q11DS) is a genetic disease known to lead to cerebral structural alterations, which we study using the framework of the macroscopic white-matter connectome. We create weighted connectomes of 44 patients with 22q11DS ...

Elsevier Sci Ltd2016

Exploring Citation Networks to Study Intertextuality in Classics

Matteo Romanello

Referring constitutes such an essential scholarly activity across disciplines that it has been regarded by [Unsworth 2000] as one of the scholarly primitives. In Classics, in particular, the references to passages of the ancient texts - the so-called canon ...

Alliance Digital Humanities Organizations2016

Is the Network Turing-Complete?

Dejan Kostic, Peter Peresini

Ensuring correct network behavior is hard. This is the case even for simple networks, and adding middleboxes only complicates this task. In this paper, we demonstrate a fundamental property of networks. Namely, we show a way of using a network to emulate t ...

2013

Rate allocation and optimized decoding in inter-session network coding

Eirina Bourtsoulatze

Recent advances in data processing and communication systems have led to a continuous increase in the amount of data communicated over today’s networks. These large volumes of data pose new challenges on the current networking infrastructure that only offe ...

EPFL2013