SMT Solvers for Neural Network Training

Previous research has confirmed that training neural networks with ReLU activations is NP-hard. A fun implication of this is that SMT solvers can be used for neural network training. This project uses an off the shelf SMT solver to train a simple feedforward neural network with ReLU activations and compares the runtime to backpropagation. The GitHub repo can be explored here.