✨ PyTorch implementation of "Cora: Correspondence-aware Image Editing Using Few-Step Diffusion", accepted at SIGGRAPH 2025.
Official Repository for different models based on MultiHead VGAEs.
An implementation of the Graph Neural Networks for the Cora dataset
MLP vs GCN — a hands-on demo of why edges matter.
OTPs have long been identified as perfect encryption, however, they have limitations that have made them impractical. MUPs (Multiple Use Pads) are reusable OTPs that are practical and ideal. This is a basic example to demonstrate that the removal of language and plaintext patterns.
Graph neural networks implemented from first principles with NumPy, including custom autograd, GCN, GAT, sparse message passing, and reproducible Cora benchmarks.
GNN 재현 실험
GAT (PyTorch Geometric) on Cora with YAML-driven CLI, tests, CI, and artifact uploads.
From-scratch Graph Convolutional Networks (Kipf & Welling, 2017): paper reproduction, MLP baseline, and over-smoothing experiments on Cora/Citeseer/Pubmed.
Repository for CoRa, a CLI which can extract radiomics from COVID-19 CT scans.
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