Supervised & unsupervised machine-learning techniques are applied to the database of weighted P4s which admit Calabi-Yau hypersurfaces.

Last update: Sep 08, 2022

Overview

Weighted Projective Spaces ML

Description:
The database of 5-vectors describing 4d weighted projective spaces which admit Calabi-Yau hypersurfaces are examined with supervised and unsupervised ML techniques.

How to run:
~ Datasets available in the folder 'Data', including the h11 clustering results.
~ Scripts related to investigations are labelled accordingly. They are run cell-by-cell sequentially with commented points to change parameters for analysis. ML is run with the use of sci-kit learn.

Owner

Ed Hirst

PhD Student at City, University of London

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Supervised & unsupervised machine-learning techniques are applied to the database of weighted P4s which admit Calabi-Yau hypersurfaces.

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Overview

Weighted Projective Spaces ML

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Ed Hirst

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Supervised & unsupervised machine-learning techniques are applied to the database of weighted P4s which admit Calabi-Yau hypersurfaces.

Related tags

Overview

Weighted Projective Spaces ML

Owner

Ed Hirst

Defending against Model Stealing via Verifying Embedded External Features

Code for the paper "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021)

Research into Forex price prediction from price history using Deep Sequence Modeling with Stacked LSTMs.

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Analysis code and Latex source of the manuscript describing the conditional permutation test of confounding bias in predictive modelling.

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