Design Philosophy of laplax

The development of laplax is guided by the following principles:

• Minimal Dependencies: The package only depends on jax, ensuring compatibility and ease of integration.

• Matrix-Free Linear Algebra: The core of our implementation revolves around efficient matrix-vector products. By passing around Python Callable objects, we maintain a loose coupling between components, allowing for easy interaction with various other packages, including linear operator libraries in jax.

• Performance and Practicality: We prioritize a performant and minimal implementation that serves practical needs. The package offers a simple API for basic use cases while primarily serving as a reference implementation for researchers to compare new methods or iterate quickly over experiments.

• PyTree-Centric Structure: Internally, the package is structured around PyTrees. This design choice allows us to defer materialization until necessary, optimizing performance and memory usage.

Roadmap and Contributions

We're developing this package in public. The roadmap and feature priorities are discussed in the Issues of the repository. If you're interested in contributing or want to see what's planned for the future, please check them out.