State of the art of visual analytics for explainable deep learning

B La Rosa, G Blasilli, R Bourqui, D Auber… - Computer Graphics …, 2023 - Wiley Online Library
The use and creation of machine‐learning‐based solutions to solve problems or reduce
their computational costs are becoming increasingly widespread in many domains. Deep …

A survey of surveys on the use of visualization for interpreting machine learning models

A Chatzimparmpas, RM Martins… - Information …, 2020 - journals.sagepub.com
Research in machine learning has become very popular in recent years, with many types of
models proposed to comprehend and predict patterns and trends in data originating from …

Visual interaction with dimensionality reduction: A structured literature analysis

D Sacha, L Zhang, M Sedlmair, JA Lee… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data.
For DR techniques to be useful in exploratory data analysis, they need to be adapted to …

Visualization and visual analysis of ensemble data: A survey

J Wang, S Hazarika, C Li… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Over the last decade, ensemble visualization has witnessed a significant development due
to the wide availability of ensemble data, and the increasing visualization needs from a …

Survey on the analysis of user interactions and visualization provenance

K Xu, A Ottley, C Walchshofer, M Streit… - Computer Graphics …, 2020 - Wiley Online Library
There is fast‐growing literature on provenance‐related research, covering aspects such as
its theoretical framework, use cases, and techniques for capturing, visualizing, and …

Increasing the transparency of research papers with explorable multiverse analyses

P Dragicevic, Y Jansen, A Sarma, M Kay… - proceedings of the 2019 …, 2019 - dl.acm.org
We present explorable multiverse analysis reports, a new approach to statistical reporting
where readers of research papers can explore alternative analysis options by interacting …

Clustervision: Visual supervision of unsupervised clustering

BC Kwon, B Eysenbach, J Verma, K Ng… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
Clustering, the process of grouping together similar items into distinct partitions, is a
common type of unsupervised machine learning that can be useful for summarizing and …

InSituNet: Deep image synthesis for parameter space exploration of ensemble simulations

W He, J Wang, H Guo, KC Wang… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
We propose InSituNet, a deep learning based surrogate model to support parameter space
exploration for ensemble simulations that are visualized in situ. In situ visualization …

Viewing visual analytics as model building

N Andrienko, T Lammarsch, G Andrienko… - Computer graphics …, 2018 - Wiley Online Library
To complement the currently existing definitions and conceptual frameworks of visual
analytics, which focus mainly on activities performed by analysts and types of techniques …

Opening the black box: Strategies for increased user involvement in existing algorithm implementations

T Mühlbacher, H Piringer, S Gratzl… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
An increasing number of interactive visualization tools stress the integration with
computational software like MATLAB and R to access a variety of proven algorithms. In …