Installation

Follow these steps to set up the project environment:

git clone https://github.com/yourusername/your-repository.git
cd your-repository

Create and activate a virtual environment:

python -m venv env
source env/bin/activate  # On Unix/macOS
venv\Scripts\activate  # On Windows

Install the required packages:

pip install -r requirements.txt

Overview

The /models folder contains the following models:

base_mon_net
- abstract base class for all monotone networks, which are implicit networks formed by repeatedly passing through same monotone layer
- based on https://github.com/locuslab/monotone_op_net/blob/master/mon.py
mon_net_AD
- monotone network trained via automatic differentation (AD)
mon_net_JFB
- monotone network trained via Jacobian free backpropagation (JFB)
- performs fixed number of iterations then backpropagates through last iteration only
mon_net_JFB_R
- monotone network trained via Jacobian free backpropagation (JFB), but with random selection of the number of iterations
mon_net_JFB_CSBO
- monotone network trained via Jacobian free backpropagation (JFB), but with random selection of the number of iterations and use of the gradient estimator $\hat{v} = \hat{v}1 + \frac{1}{p_k}(\hat{v}{k+1}-\hat{v}_k)$
- inspired by https://arxiv.org/abs/2310.18535