Results 151 to 160 of about 550 (233)

L‐VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts

open access: yesComputer Graphics Forum, EarlyView.
L‐VISP is a human‐machine solution that uses visual analytics for LSTM modelling in clinical research. L‐VISP uses custom visual encodings to make multiple LSTM variants interpretable, supporting a full range of analysis, from understanding model operations and evaluating performance to interpreting results in a clinical context.
C. Floricel   +6 more
wiley   +1 more source

Implicit learning of recursive context-free grammars. [PDF]

open access: yesPLoS One, 2012
Rohrmeier M, Fu Q, Dienes Z.
europepmc   +1 more source

BloomTree: Dynamic Coloring Techniques for Exploring Deep and Wide Tree Structures

open access: yesComputer Graphics Forum, EarlyView.
Abstract This study introduces BloomTree, an interactive Sunburst system for visualizing massive hierarchical datasets, such as the Tree of Life. Traditional static color schemes fail to maintain perceptual distinguishability when applied to millions of nodes, and managing the full tree in memory is computationally costly.
A. Tanaka, K. Wakita
wiley   +1 more source

TerraTinker: Crafting Playful Geospatial Visualizations

open access: yesComputer Graphics Forum, EarlyView.
Abstract With the onset of digital technologies, conveying information to the young generation is becoming evermore challenging, forcing us to explore alternative methods, such as using video games. A typical area that could benefit from innovation is geography, where we want to convey the relationship between selected geographical locations and ...
J. Rosecký   +3 more
wiley   +1 more source

Scalable Computation of Topological Abstractions for Scalar Data

open access: yesComputer Graphics Forum, EarlyView.
Abstract Topological data analysis has become an important tool for large scale scalar data analysis and visualization, efficiently extracting the inherent structure and features of interest of the data. However, with growing dataset sizes and complexity, it is increasingly becoming infeasible to compute topological abstractions of interest in serial ...
M. Will   +6 more
wiley   +1 more source

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