Deep Learning Test
Implementing deep learning in Rust using just a linear algebra library (nalgebra). The neural network (4 hidden layers, 32 neurons per layer) attempts to reconstruct a 512x512 image. It takes a 2D position as input, and outputs an RGB value.
Training time is around one minute, which is suprisingly quick considering that no parallelism or GPU acceleration is involved. Here is the reference image:
and here is the reconstruction from the neural network:
Note that I implemented Fourier features, as described here to improve reconstruction quality. Without this, here's what the reconstruction looks like: