The state of the art in enhancing trust in machine learning models with the use of visualizations
Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …
Toward a quantitative survey of dimension reduction techniques
Dimensionality reduction methods, also known as projections, are frequently used in
multidimensional data exploration in machine learning, data science, and information …
multidimensional data exploration in machine learning, data science, and information …
Visualizing high-dimensional data: Advances in the past decade
Massive simulations and arrays of sensing devices, in combination with increasing
computing resources, have generated large, complex, high-dimensional datasets used to …
computing resources, have generated large, complex, high-dimensional datasets used to …
Fundamental controls on fluid flow in carbonates: current workflows to emerging technologies
SM Agar, S Geiger - Geological Society, London, Special …, 2015 - lyellcollection.org
The introduction reviews topics relevant to the fundamental controls on fluid flow in
carbonate reservoirs and to the prediction of reservoir performance. The review provides …
carbonate reservoirs and to the prediction of reservoir performance. The review provides …
A survey of human‐centered evaluations in human‐centered machine learning
Visual analytics systems integrate interactive visualizations and machine learning to enable
expert users to solve complex analysis tasks. Applications combine techniques from various …
expert users to solve complex analysis tasks. Applications combine techniques from various …
Evaluation of sampling methods for scatterplots
Given a scatterplot with tens of thousands of points or even more, a natural question is which
sampling method should be used to create a small but “good” scatterplot for a better …
sampling method should be used to create a small but “good” scatterplot for a better …
A visual interaction framework for dimensionality reduction based data exploration
M Cavallo, Ç Demiralp - Proceedings of the 2018 CHI Conference on …, 2018 - dl.acm.org
Dimensionality reduction is a common method for analyzing and visualizing high-
dimensional data. However, reasoning dynamically about the results of a dimensionality …
dimensional data. However, reasoning dynamically about the results of a dimensionality …
Automatic scatterplot design optimization for clustering identification
GJ Quadri, JA Nieves, BM Wiernik… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Scatterplots are among the most widely used visualization techniques. Compelling
scatterplot visualizations improve understanding of data by leveraging visual perception to …
scatterplot visualizations improve understanding of data by leveraging visual perception to …
[HTML][HTML] Quantitative and qualitative comparison of decision-map techniques for explaining classification models
Visualization techniques for understanding and explaining machine learning models have
gained significant attention. One such technique is the decision map, which creates a 2D …
gained significant attention. One such technique is the decision map, which creates a 2D …
Unprojection: Leveraging inverse-projections for visual analytics of high-dimensional data
Projection techniques are often used to visualize high-dimensional data, allowing users to
better understand the overall structure of multi-dimensional spaces on a 2D screen …
better understand the overall structure of multi-dimensional spaces on a 2D screen …