Results 151 to 160 of about 550 (233)
L‐VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts
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]
Rohrmeier M, Fu Q, Dienes Z.
europepmc +1 more source
BloomTree: Dynamic Coloring Techniques for Exploring Deep and Wide Tree Structures
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
The laws of natural deduction in inference by DNA computer. [PDF]
Rogowski L, Sosík P.
europepmc +1 more source
TerraTinker: Crafting Playful Geospatial Visualizations
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
Neural networks for abstraction and reasoning. [PDF]
Bober-Irizar M, Banerjee S.
europepmc +1 more source
Data Compression Concepts and Algorithms and their Applications to Bioinformatics. [PDF]
Nalbantog̃lu OU, Russell DJ, Sayood K.
europepmc +1 more source
Scalable Computation of Topological Abstractions for Scalar Data
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

