Understanding the temporal evolution of topological features by means of tracking graphs is a common task, often performed using scalar field analysis. However, these graphs are either hard to interpret or capture information at a very high level that is not intuitive to the user. To bridge this gap, we propose persistenceBundles, a hierarchical edge-bundling approach for visualizing tracked features using persistence hierarchies. We demonstrate the effectiveness of our approach using the viscous finger dataset
Acknowledgments We gratefully acknowledge Roel Neggers for providing the DALES simulation data. JLS ...
In recent years there has been noticeable interest in the study of the “shape of data”. Among the ma...
This system paper presents the Topology ToolKit (TTK), a software platform designed for the topologi...
Understanding the temporal evolution of topological features by means of tracking graphs is a common...
This manuscript presents a topology-based analysis and visualization framework that enables the effe...
<p>In this thesis, we explore techniques in statistics and persistent homology, which detect feature...
International audiencePersistence diagrams, the most common descriptors of Topological Data Analysis...
This dissertation studies persistence diagrams and their usefulness in machine learning. Persistence...
In recent years there has been noticeable interest in the study of the "shape of data". Among the m...
One of the critical tools of persistent homology is the persistence diagram. We demonstrate the appl...
In topological data analysis and visualization, topological descriptors such as persistence diagrams...
Persistence is a theory for Topological Data Analysis based on analyzing the scale at whichtopologic...
Tracking graphs are a well established tool in topological analysis to visualize the evolution of co...
Abstract. Persistence landscapes can be used to analyze large families of large persistence di-agram...
the Netherlands Abstract — Depicting change captured by dynamic graphs and temporal paths, or trails...
Acknowledgments We gratefully acknowledge Roel Neggers for providing the DALES simulation data. JLS ...
In recent years there has been noticeable interest in the study of the “shape of data”. Among the ma...
This system paper presents the Topology ToolKit (TTK), a software platform designed for the topologi...
Understanding the temporal evolution of topological features by means of tracking graphs is a common...
This manuscript presents a topology-based analysis and visualization framework that enables the effe...
<p>In this thesis, we explore techniques in statistics and persistent homology, which detect feature...
International audiencePersistence diagrams, the most common descriptors of Topological Data Analysis...
This dissertation studies persistence diagrams and their usefulness in machine learning. Persistence...
In recent years there has been noticeable interest in the study of the "shape of data". Among the m...
One of the critical tools of persistent homology is the persistence diagram. We demonstrate the appl...
In topological data analysis and visualization, topological descriptors such as persistence diagrams...
Persistence is a theory for Topological Data Analysis based on analyzing the scale at whichtopologic...
Tracking graphs are a well established tool in topological analysis to visualize the evolution of co...
Abstract. Persistence landscapes can be used to analyze large families of large persistence di-agram...
the Netherlands Abstract — Depicting change captured by dynamic graphs and temporal paths, or trails...
Acknowledgments We gratefully acknowledge Roel Neggers for providing the DALES simulation data. JLS ...
In recent years there has been noticeable interest in the study of the “shape of data”. Among the ma...
This system paper presents the Topology ToolKit (TTK), a software platform designed for the topologi...