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Supplementary code for the PhD thesis "Geometric Perspectives on Graph-based Learning Algorithms"

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Geometric Perspectives on Graph-based Learning Algorithms

This repository contains supplementary materials for the PhD thesis titled "Geometric Perspectives on Graph-based Learning Algorithms".

Summary

  1. Dynamics of the accelerated t-SNE

  2. Sobolev Ricci Curvature

Repository structure

Directory Description
Dynamics_of_the_accelerated_t-SNE/ Code and notebooks for the accelerated t-SNE experiments, including GD/MM/NAG comparisons, ARR computation, and additional experiments for the dissertation.
Dynamics_of_the_accelerated_t-SNE/experiments/ Scripts for ARR-stopped continuous relaxations, comparison with discrete t-SNE, KL-divergence trajectories, and momentum sweep experiments.
SobolevRicciCurvature/community_detection/ Community-detection experiments using SRC/ORC, including SBM, LFR, real graph datasets, ablation studies, and cycle-controlled ORC--SRC discrepancy experiments.
SobolevRicciCurvature/manl/ MANL / edge-pruning experiments using ORC and SRC variants.

Reproducing dissertation experiments

The code is organized by dissertation topic.

  • For Chapter 3, see Dynamics_of_the_accelerated_t-SNE/experiments/README_tsne.md. This includes ARR computation, ARR-stopped continuous relaxations, comparison with the original discrete t-SNE update, KL-divergence trajectories, and momentum-sweep experiments.
  • For Chapter 4 community-detection experiments, see SobolevRicciCurvature/community_detection/README.md.
  • For Chapter 4 MANL / edge-pruning experiments, see SobolevRicciCurvature/manl/README.md.

Citation

If you use this repository, please cite the corresponding dissertation or the related papers listed above. A formal citation will be added after the dissertation is published.

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Supplementary code for the PhD thesis "Geometric Perspectives on Graph-based Learning Algorithms"

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