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Found 4 papers, 2 papers with code
Euler Characteristic Surfaces
While topological data analysis of higher-dimensional parameter spaces using stronger invariants such as homology continues to be the subject of intense research, Euler characteristic is more manageable theoretically and computationally, and this analysis can be seen as an important intermediary step in multi-parameter topological data analysis.
Topological Data Analysis
Algebraic Topology
Computational Geometry
Automated Segmentation of Optical Coherence Tomography Angiography Images: Benchmark Data and Clinically Relevant Metrics
Our results show that, for the set of images considered, deep learning architectures (U-Net and CS-Net) achieve the best performance.
Convolutional neural networks for structured omics: OmicsCNN and the OmicsConv layer
Convolutional Neural Networks (CNNs) are a popular deep learning architecture widely applied in different domains, in particular in classifying over images, for which the concept of convolution with a filter comes naturally.
Phylogenetic Convolutional Neural Networks in Metagenomics
We introduce here Ph-CNN, a novel deep learning architecture for the classification of metagenomics data based on the Convolutional Neural Networks, with the patristic distance defined on the phylogenetic tree being used as the proximity measure.
