This repository implements a deep learning approach for reconstructing 3D surfaces from point cloud data. The method optimizes a neural network to solve the eikonal equation, using the input point cloud as a boundary condition to find a signed distance function (SDF). The implicit geometric regularization guides the optimization toward natural solutions for shape representation. The implementation uses PyTorch and supports various point cloud formats including xyz, npy, npz, and ply files.