A q-quantile estimator for high-dimensional distributions
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Updated
Jul 30, 2018 - Python
A q-quantile estimator for high-dimensional distributions
Lossless conversion algorithm for converting Cortical Learning Algorithm binary vectors to Modular Composite Representation vectors. Implements Integer Sparse Distributed Memory.
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A fast, accurate, and modularized dimensionality reduction approach based on diffusion harmonics and graph layouts. Escalates to millions of samples on a personal laptop. Adds high-dimensional big data intrinsic structure to your clustering and data visualization workflow.
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Implements "Clustering a Million Faces by Identity"
Simple and efficient Python package for modeling d-dimensional Bravais lattices in solid state physics.
[TMLR' 24] High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy
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