Zobrazeno 1 - 10
of 868
pro vyhledávání: '"Kerren, A."'
Autor:
Fujiwara, Takanori, Kucher, Kostiantyn, Wang, Junpeng, Martins, Rafael M., Kerren, Andreas, Ynnerman, Anders
Research in ML4VIS investigates how to use machine learning (ML) techniques to generate visualizations, and the field is rapidly growing with high societal impact. However, as with any computational pipeline that employs ML processes, ML4VIS approach
Externí odkaz:
http://arxiv.org/abs/2409.02485
Embeddings are powerful tools for transforming complex and unstructured data into numeric formats suitable for computational analysis tasks. In this work, we use multiple embeddings for similarity calculations to be applied in bibliometrics and scien
Externí odkaz:
http://arxiv.org/abs/2409.00478
Comparing directed acyclic graphs is essential in various fields such as healthcare, social media, finance, biology, and marketing. DAGs often result from contagion processes over networks, including information spreading, retweet activity, disease t
Externí odkaz:
http://arxiv.org/abs/2406.05560
Visualization for explainable and trustworthy machine learning remains one of the most important and heavily researched fields within information visualization and visual analytics with various application domains, such as medicine, finance, and bioi
Externí odkaz:
http://arxiv.org/abs/2403.12005
Autor:
Feyer, Stefan P., Pinaud, Bruno, Kobourov, Stephen G., Brich, Nicolas, Krone, Michael, Kerren, Andreas, Behrisch, Michael, Schreiber, Falk, Klein, Karsten
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics, In press, To appear. Accepted to IEEE VIS 2023
Relational information between different types of entities is often modelled by a multilayer network (MLN) -- a network with subnetworks represented by layers. The layers of an MLN can be arranged in different ways in a visual representation, however
Externí odkaz:
http://arxiv.org/abs/2307.10674
As the complexity of machine learning (ML) models increases and their application in different (and critical) domains grows, there is a strong demand for more interpretable and trustworthy ML. A direct, model-agnostic, way to interpret such models is
Externí odkaz:
http://arxiv.org/abs/2304.00133
The design of intuitive three-dimensional user interfaces is vital for interaction in virtual reality, allowing to effectively close the loop between a human user and the virtual environment. The utilization of 3D gestural input allows for useful han
Externí odkaz:
http://arxiv.org/abs/2303.07995
The use of head-mounted display technologies for virtual reality experiences is inherently single-user-centred, allowing for the visual immersion of its user in the computer-generated environment. This isolates them from their physical surroundings,
Externí odkaz:
http://arxiv.org/abs/2303.07899
Publikováno v:
Computer Graphics Forum 2020, 39(3), 713-756
Machine learning (ML) models are nowadays used in complex applications in various domains, such as medicine, bioinformatics, and other sciences. Due to their black box nature, however, it may sometimes be hard to understand and trust the results they
Externí odkaz:
http://arxiv.org/abs/2212.11737
We present a case study investigating feature descriptors in the context of the analysis of chemical multivariate ensemble data. The data of each ensemble member consists of three parts: the design parameters for each ensemble member, field data resu
Externí odkaz:
http://arxiv.org/abs/2212.03731