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.
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.