Results 271 to 280 of about 1,043,448 (307)

Graphcode: Learning from multiparameter persistent homology using graph neural networks

Neural Information Processing Systems
We introduce graphcodes, a novel multi-scale summary of the topological properties of a dataset that is based on the well-established theory of persistent homology. Graphcodes handle datasets that are filtered along two real-valued scale parameters. Such
Michael Kerber, Florian Russold
semanticscholar   +1 more source

Boosting Graph Pooling with Persistent Homology

Neural Information Processing Systems
Recently, there has been an emerging trend to integrate persistent homology (PH) into graph neural networks (GNNs) to enrich expressive power. However, naively plugging PH features into GNN layers always results in marginal improvement with low ...
Chaolong Ying, Xinjian Zhao, Tianshu Yu
semanticscholar   +1 more source

Persistent homology and topological statistics of hyperuniform point clouds

Physical Review Research
Hyperuniformity, the suppression of density fluctuations at large length scales, is observed across a wide variety of domains, from cosmology to condensed matter and biological systems.
M. Salvalaglio, Dominic J. Skinner, Jörn Dunkel, Axel Voigt   +3 more
semanticscholar   +1 more source

Descriptor generation from Morgan fingerprint using persistent homology

SAR and QSAR in environmental research (Print)
In cheminformatics, molecular fingerprints (FPs) are used in various tasks such as regression and classification. However, predictive models often underutilize Morgan FP for regression and related tasks in machine learning.
T. Ehiro
semanticscholar   +1 more source

The Persistence Space in Multidimensional Persistent Homology

2013
Multidimensional persistent modules do not admit a concise representation analogous to that provided by persistence diagrams for real-valued functions. However, there is no obstruction for multidimensional persistent Betti numbers to admit one. Therefore, it is reasonable to look for a generalization of persistence diagrams concerning those properties ...
Andrea Cerri, LANDI, Claudia
openaire   +2 more sources

Persistence Cycles for Visual Exploration of Persistent Homology

IEEE Transactions on Visualization and Computer Graphics, 2022
Persistent homology is a fundamental tool in topological data analysis used for the most diverse applications. Information captured by persistent homology is commonly visualized using scatter plots representations. Despite being widely adopted, such a visualization technique limits user understanding and is prone to misinterpretation.
openaire   +2 more sources

Persistent homology in tourism

Tourism Management, 2020
Marketing a destination is costly so efficiency of promotion expenditure is critical; identifying improved techniques to achieve this will be of great value. Clustering techniques have sought to identify target markets but are widely criticised for the biases they induce.
Chong, Woonkian, Rudkin, Simon
openaire   +1 more source

Persistent-homology-based machine learning: a survey and a comparative study

Artificial Intelligence Review, 2022
Chi Seng Pun, S. Lee, Kelin Xia
semanticscholar   +1 more source

Functional Distinction between Human and Mouse Sodium-Coupled Citrate Transporters and Its Biologic Significance: An Attempt for Structural Basis Using a Homology Modeling Approach

Chemical Reviews, 2021
Vadivel Ganapathy
exaly  

Learning discriminative topological structure information representation for 2D shape and social network classification via persistent homology

Knowledge-Based Systems
Changshuo Wang, Rongsheng Cao, Ruiping Wang   +2 more
semanticscholar   +1 more source