A topological cell-openness index τ derived from Betti numbers is introduced to characterize open and closed cells in porous materials as an alternative to gas pycnometry.
Topology and data.Bulletin of the American Mathematical Society, 46(2):255–308
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L-fuzzy simplicial homology generalizes simplicial homology to L-fuzzy subcomplexes by assigning values from a completely distributive lattice L to simplices and deriving associated homology modules.
A patch-based TDA approach for CT volumes outperforms cubical complex persistent homology and radiomic features in classification accuracy while reducing computation time.
ABot-M0 unifies heterogeneous robot data into a 6-million-trajectory dataset and introduces Action Manifold Learning to predict stable actions on a low-dimensional manifold using a DiT backbone.
Dimension-reduced topological features from multichannel iEEG achieve up to 80% balanced accuracy in three-class seizure-state classification across 55 patients, with classical models matching deep learning performance.
Simplex2Vec embeddings are used to compute and visualize community structures in simplicial complexes, with tests on synthetic data and applications to social and brain datasets showing benefits from higher-order interactions.
citing papers explorer
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Topological cell-openness index for porous materials
A topological cell-openness index τ derived from Betti numbers is introduced to characterize open and closed cells in porous materials as an alternative to gas pycnometry.
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L-fuzzy simplicial homology
L-fuzzy simplicial homology generalizes simplicial homology to L-fuzzy subcomplexes by assigning values from a completely distributive lattice L to simplices and deriving associated homology modules.
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A Novel Patch-Based TDA Approach for Computed Tomography Imaging
A patch-based TDA approach for CT volumes outperforms cubical complex persistent homology and radiomic features in classification accuracy while reducing computation time.
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ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning
ABot-M0 unifies heterogeneous robot data into a 6-million-trajectory dataset and introduces Action Manifold Learning to predict stable actions on a low-dimensional manifold using a DiT backbone.
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Classification of Epileptic iEEG using Topological Machine Learning
Dimension-reduced topological features from multichannel iEEG achieve up to 80% balanced accuracy in three-class seizure-state classification across 55 patients, with classical models matching deep learning performance.
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Simplex2Vec embeddings for community detection in simplicial complexes
Simplex2Vec embeddings are used to compute and visualize community structures in simplicial complexes, with tests on synthetic data and applications to social and brain datasets showing benefits from higher-order interactions.