A flexible and efficient С++ template library for dimension reduction
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Updated
Jun 17, 2024 - C++
A flexible and efficient С++ template library for dimension reduction
A header-only C++ library for sketching in randomized linear algebra
A fast, scalable and light-weight C++ Fréchet and DTW distance library, exposed to python and focused on clustering of polygonal curves.
DR.SC: Joint dimension reduction and spatial clustering for single-cell/spatial transcriptomics data
Autoencoder dimensionality reduction, EMD-Manhattan metrics comparison and classifier based clustering on MNIST dataset
Neural Principal Component Analysis
Algorithmic problem-solving project using autoencoders for dimension reduction, nearest neighbor search algorithms, and K-means clustering. Developed as part of a university course on software development for algorithmic problems.
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