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Found 3 papers, 2 papers with code
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks
Despite their successful application to a variety of tasks, neural networks remain limited, like other machine learning methods, by their sensitivity to shifts in the data: their performance can be severely impacted by differences in distribution between the data on which they were trained and that on which they are deployed.
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds
The use of topological descriptors in modern machine learning applications, such as Persistence Diagrams (PDs) arising from Topological Data Analysis (TDA), has shown great potential in various domains.
Image analysis for Alzheimer's disease prediction: Embracing pathological hallmarks for model architecture design
Alzheimer's disease (AD) is associated with local (e. g. brain tissue atrophy) and global brain changes (loss of cerebral connectivity), which can be detected by high-resolution structural magnetic resonance imaging.
