Dinf is discriminator-based inference for population genetics. It uses a neural network to discriminate between a target dataset and a simulated dataset. Inference is done by finding simulation parameters that produce data closely matching the target dataset. Dinf provides a Python API for creating simulation models, and a CLI for discriminator training and inference.
See the documentation for details. https://racimolab.github.io/dinf/