This repository contains the code for Interface Laplace Learning: Learnable Interface Term Helps Semi-Supervised Learning
NumPy, SciPy and PyTorch. Scipy is for sparse matrix calculation. PyTorch is for acceleration of matrix multiplication on gpu. The code is tested on the following version:
numpy==1.26.4
scipy==1.11.4
torch==2.2.1
data/ contains pretrained extracted features of each dataset. The files are collected from GraphLearning package without any change, but renamed for clarity.
inter_laplace.py includes the main function to perform training and inference.
utils.py includes utility functions.
preprocess.py includes the preprocess functions to get T, interface index and A.
The optimal parameters are provided in the appendix. Should take less than 1 second for each trial on gpu.
python inter_laplace.py --dataset mnist --label_num 1 --k_hop 4 --ridge 0.03