MOLPIPx

MOLPIPx seamlessly integrates Permutationally Invariant Polynomials (PIPs) with modern machine learning frameworks. Built on JAX and EnzymeAD-Rust, it enables efficient, differentiable modeling of potential energy surfaces using linear models, neural networks, and Gaussian processes.

MOLPIPx Diagram

Capabilities at a Glance

MOLPIPx currently includes the following implementations:

Model Type

Energy

Forces

Linear Models

Neural Networks (Flax)

Gaussian Processes (GP)

Anisotropic Models

Check the Tutorials for more information.

Documentation for the source code can be found here. The full source code with examples and tests can be explored at github.