Free Vibration Characteristics of FG-CNTRC Conical-Cylindrical Combined Shells Resting on Elastic Foundations Using the Haar Wavelet Discretization Method. [PDF]
Fan J +6 more
europepmc +1 more source
Hierarchical Optimization of the As‐Rigid‐As‐Possible Energy
Abstract The As‐Rigid‐As‐Possible (ARAP) energy [SA07] has become a versatile ingredient in various geometry processing and machine learning methods. The classic method for its minimization is a block coordinate descent, alternating between local rotation estimation and a global linear solve, which converges slowly for large problem instances.
Hendrik Meyer, Bernd Bickel, Marc Alexa
wiley +1 more source
Predicting students' performance on geometric problem-solving tasks: the roles of cognitive reflection, fluid intelligence, and mathematical beliefs. [PDF]
Rubio-Sánchez A +2 more
europepmc +1 more source
Quantitative Metrics for Edge Bundling of Network Visualizations
Abstract Edge bundling is widely used for reducing visual clutter in large 2D network and trajectory visualizations. Various edge bundling methods have been proposed, each producing qualitatively distinct outputs for the same data; however, few quantitative metrics exist for systematic evaluation. In this paper, we propose a set of quantitative metrics
M. Wallinger +3 more
wiley +1 more source
Relativistic triangle-curvature computing for federated HIV-1 protein-sequence monitoring. [PDF]
Villalba-Díez J, González-Marcos A.
europepmc +1 more source
Abstract Recent advances in AI enable the automatic generation of visualizations directly from textual prompts using agentic workflows. However, visualizations produced via one‐shot generative methods often suffer from insufficient quality, typically requiring a human in the loop to refine the outputs.
Roxana Bujack +4 more
wiley +1 more source
Class Angular Distortion Index for Dimensionality Reduction
Abstract Dimensionality reduction (DR) techniques are often characterized by whether they preserve global, high‐level structures in the data or local, neighborhood structures. This distinction matters in visualization: global methods can obscure clusters while local methods can over‐emphasize them.
Kaviru Gunaratne +2 more
wiley +1 more source
Maximum likelihood estimation of log-affine models using detailed-balanced reaction networks. [PDF]
Henriksson O +3 more
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

