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Found 7 papers, 3 papers with code
Topological Learning for Motion Data via Mixed Coordinates
Topology can extract the structural information in a dataset efficiently.
Multiple Hypothesis Testing with Persistent Homology
Multiple hypothesis testing requires a control procedure.
Generalized Penalty for Circular Coordinate Representation
We provide simulation experiments and real data analysis to support our claim that circular coordinates with generalized penalty will detect the change in high-dimensional datasets under different sampling schemes while preserving the topological structures.
Certified Mapper: Repeated testing for acyclicity and obstructions to the nerve lemma
The Mapper algorithm does not include a check for whether the cover produced conforms to the requirements of the nerve lemma.
Fibres of Failure: Classifying errors in predictive processes
We describe Fibres of Failure (FiFa), a method to classify failure modes of predictive processes using the Mapper algorithm from Topological Data Analysis.
Automatic recognition and tagging of topologically different regimes in dynamical systems
These models are often high-dimensional and chaotic.
Dualities in persistent (co)homology
We consider sequences of absolute and relative homology and cohomology groups that arise naturally for a filtered cell complex.
Algebraic Topology Computational Geometry
