discriminator-based inference for population genetics
Project description
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/
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