Outtweeting the Twitterers - Predicting Information Cascades in Microblogs

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Graph Neural Networks (GNNs) have emerged as a powerful tool for learning on graphs, demonstrating exceptional performance in various domains. However, as GNNs become increasingly popular, new challenges arise. One of the most pressing is the need to ensur ...

The adaptive social learning paradigm helps model how networked agents are able to form opinions on a state of nature and track its drifts in a changing environment. In this framework, the agents repeatedly update their beliefs based on private observation ...

The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

Network alignment is the task of identifying topologically and semantically similar nodes across (two) different networks. It plays an important role in various applications ranging from social network analysis to bioinformatic network interactions. Howeve ...

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

Over the past decade, interatomic potentials based on machine learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure calculations, they inherit ...

Goods can exhibit positive externalities impacting decisions of customers in social networks. Suppliers can integrate these externalities in their pricing strategies to increase their revenue. Besides optimizing the prize, suppliers also have to consider t ...

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, ...

Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

Non-fungible tokens (NFTs) as a decentralized proof of ownership represent one of the main reasons why Ethereum is a disruptive technology. This paper presents the first systematic study of the interactions occurring in a number of NFT ecosystems. We illus ...

Information retrieval (IR) systems such as search engines are important for people to find what they need among the tremendous amount of data available in their organization or on the Internet. These IR systems enable users to search in a large data collec ...

Despite governing heat management in any realistic device, the microscopic mechanisms of heat transport in all-solid-state electrolytes are poorly known: existing calculations, all based on simplistic semi-empirical models, are unreliable for superionic co ...

A graph is a versatile data structure facilitating representation of interactions among objects in various complex systems. Very often these objects have attributes whose measurements change over time, reflecting the dynamics of the system. This general da ...

The majority of currently available webpages are dynamic in nature and are changing frequently. New content gets added to webpages, and existing content gets updated or deleted. Hence, people find it useful to be alert for changes in webpages that contain ...

Deep Neural Networks (DNNs) have achieved great success in a wide range of applications, such as image recognition, object detection, and semantic segmentation. Even though the discriminative power of DNNs is nowadays unquestionable, serious concerns have ...

Studying real-world networks such as social networks or web networks is a challenge. These networks often combine a complex, highly connected structure together with a large size. We propose a new approach for large scale networks that is able to automatic ...

The automatic recognition of food on images has numerous interesting applications, including nutritional tracking in medical cohorts. The problem has received significant research attention, but an ongoing public benchmark on non-biased (i.e., not scraped ...

Cancer diagnosis, prognosis, and therapy response predictions from tissue specimens highly depend on the phenotype and topological distribution of constituting histological entities. Thus, adequate tissue representations for encoding histological entities ...

Deletion is a core facet of Online Social Networks (OSNs). For users, deletion is a tool to remove what they have shared and control their data. For OSNs, robust deletion is both an obligation to their users and a risk when developer mistakes inevitably oc ...

Wikipedia is a rich and invaluable source of information. Its central place on the Web makes it a particularly interesting object of study for scientists. Researchers from different domains used various complex datasets related to Wikipedia to study langua ...

Outtweeting the Twitterers - Predicting Information Cascades in Microblogs

Chattez avec Graph Search

Privacy-Preserving Machine Learning on Graphs

Discovering Influencers in Opinion Formation Over Social Graphs

A new age in protein design empowered by deep learning

Network Alignment With Holistic Embeddings

Caching and Neutrality

Beyond potentials: Integrated machine learning models for materials

Maintenance scheduling of manufacturing systems based on optimal price of the network

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

Dynamic Personalized Ranking

Networks of Ethereum Non-Fungible Tokens: A graph-based analysis of the ERC-721 ecosystem

Graph Embedding for Retrieval

Temperature- and vacancy-concentration-dependence of heat transport in Li3ClO from multi-method numerical simulations

Dynamic pattern recognition in large-scale graphs with applications to social networks

Change Detection and Notification of Web Pages: A Survey

Understanding Deep Neural Networks using Adversarial Attacks

Spikyball Sampling: Exploring Large Networks via an Inhomogeneous Filtered Diffusion

The Food Recognition Benchmark: Using Deep Learning to Recognize Food in Images

Hierarchical graph representations in digital pathology

DELF: Safeguarding deletion correctness in Online Social Networks

A Graph-structured Dataset for Wikipedia Research