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Many real-world systems exhibit temporal, dynamic behaviors, which are captured as time series of complex agent interactions. To perform temporal reasoning, current methods primarily encode temporal dynamics through simple sequence-based…

Machine Learning · Computer Science 2024-01-09 Paridhi Maheshwari , Hongyu Ren , Yanan Wang , Rok Sosic , Jure Leskovec

Embedding static graphs in low-dimensional vector spaces plays a key role in network analytics and inference, supporting applications like node classification, link prediction, and graph visualization. However, many real-world networks…

Machine Learning · Computer Science 2021-07-23 Claudio D. T. Barros , Matheus R. F. Mendonça , Alex B. Vieira , Artur Ziviani

Many tasks in graph machine learning, such as link prediction and node classification, are typically solved by using representation learning, in which each node or edge in the network is encoded via an embedding. Though there exists a lot…

Dynamic or temporal networks enable representation of time-varying edges between nodes. Conventional adjacency-based data structures used for storing networks such as adjacency lists were designed without incorporating time and can thus…

Social and Information Networks · Computer Science 2022-06-24 Tanner Hilsabeck , Makan Arastuie , Kevin S. Xu

Temporal network analysis and time evolution of network characteristics are powerful tools in describing the changing topology of dynamic networks. This paper uses such approaches to better visualize and provide analytical measures for the…

Multiagent Systems · Computer Science 2021-10-04 N. DiBrita , K. Eledlebi , H. Hildmann , L. Culley , A. F. Isakovic

Learning graph representations is a fundamental task aimed at capturing various properties of graphs in vector space. The most recent methods learn such representations for static networks. However, real world networks evolve over time and…

Social and Information Networks · Computer Science 2019-08-22 Palash Goyal , Sujit Rokka Chhetri , Arquimedes Canedo

Node-link diagrams are widely used to visualise networks. However, even the best network layout algorithms ultimately result in 'hairball' visualisations when the graph reaches a certain degree of complexity, requiring simplification…

Human-Computer Interaction · Computer Science 2021-03-25 Vahan Yoghourdjian , Yalong Yang , Tim Dwyer , Lee Lawrence , Michael Wybrow , Kim Marriott

Integrating intelligent systems, such as robots, into dynamic group settings poses challenges due to the mutual influence of human behaviors and internal states. A robust representation of social interaction dynamics is essential for…

Human-Computer Interaction · Computer Science 2024-06-11 J. Taery Kim , Archit Naik , Isuru Jayarathne , Sehoon Ha , Jouh Yeong Chew

We present a method for visualising the response of a deep neural network to a specific input. For image data for instance our method will highlight areas that provide evidence in favor of, and against choosing a certain class. The method…

Computer Vision and Pattern Recognition · Computer Science 2017-06-13 Luisa M. Zintgraf , Taco S. Cohen , Max Welling

In this short essay, we show how computer experiments, and especially visualization, allowed for the investigation and discovery of phenomena which would have passed unnoticed. We shall also highlight the importance of interactivity between…

History and Overview · Mathematics 2022-03-22 J. -R. Chazottes , M. Monticelli

Systematic reviews provide comprehensive syntheses of research fields. As a result, systematic reviews often emphasize synthesizing across the large bodies of literature rather than just describing the studies from which the conclusions…

Egocentric networks, often visualized as node-link diagrams, portray the complex relationship (link) dynamics between an entity (node) and others. However, common analytics tasks are multifaceted, encompassing interactions among four key…

Human-Computer Interaction · Computer Science 2025-03-07 Yun-Hsin Kuo , Dongyu Liu , Kwan-Liu Ma

Multi-faceted data visualization typically involves several dedicated views. To create a comprehensive understanding of the data, users have to mentally integrate the information from the different views. This integration is hindered by…

Human-Computer Interaction · Computer Science 2025-07-23 Abdulhaq Adetunji Salako , Hannes Hagen , Christian Tominski

For any stream of time-stamped edges that form a dynamic network, an important choice is the aggregation granularity that an analyst uses to bin the data. Picking such a windowing of the data is often done by hand, or left up to the…

Social and Information Networks · Computer Science 2017-02-28 Benjamin Fish , Rajmonda S. Caceres

Temporal graphs represent the dynamic relationships among entities and occur in many real life application like social networks, e commerce, communication, road networks, biological systems, and many more. They necessitate research beyond…

Machine Learning · Computer Science 2022-08-26 Shubham Gupta , Srikanta Bedathur

The temporal dynamics of a complex system such as a social network or a communication network can be studied by understanding the patterns of link appearance and disappearance over time. A critical task along this understanding is to…

Social and Information Networks · Computer Science 2018-04-17 Mahmudur Rahman , Tanay Kumar Saha , Mohammad Al Hasan , Kevin S. Xu , Chandan K. Reddy

Explanations for computer vision models are important tools for interpreting how the underlying models work. However, they are often presented in static formats, which pose challenges for users, including information overload, a gap between…

Human-Computer Interaction · Computer Science 2025-04-16 Indu Panigrahi , Sunnie S. Y. Kim , Amna Liaqat , Rohan Jinturkar , Olga Russakovsky , Ruth Fong , Parastoo Abtahi

Observing the relationship between two or more variables over space and time is essential in many domains. For instance, looking, for different countries, at the evolution of both the life expectancy at birth and the fertility rate will…

Human-Computer Interaction · Computer Science 2019-10-16 Vanessa Peña-Araya , Emmanuel Pietriga , Anastasia Bezerianos

The paper presents a 3D interactive representation of fairly large picture collections which facilitates browsing through unstructured sets of icons or pictures. Implementation of this representation implies choosing between two…

Human-Computer Interaction · Computer Science 2007-08-27 Olivier Christmann , Noëlle Carbonell

Investigating the frequency and distribution of small subgraphs with a few nodes/edges, i.e., motifs, is an effective analysis method for static networks. Motif-driven analysis is also useful for temporal networks where the spectrum of…

Social and Information Networks · Computer Science 2021-05-04 Penghang Liu , Valerio Guarrasi , A. Erdem Sarıyüce
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