Major refactor - switch to JAX and add polynomials + use Schur complement to solve - #9
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- Add polynomial-augmented RBF system with Schur complement solver - Use Cholesky factorization for efficient solve (replaces pinv) - Add poly_degree config option (0=none, 1=linear, 2=quadratic, default=2) - Add poly_coeffs and poly_degree fields to ModelState - Update save/load for backward compatibility with old models - Update examples to show poly_degree parameter - Add comprehensive tests for new functionality 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add comprehensive CI/CD setup with: - Test matrix for Python 3.10, 3.11, 3.12 on Ubuntu - Codecov integration for code coverage reporting - Pip caching for faster workflow runs - JAX CPU-only installation for CI environment - Status badges in README 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
…hing - Replace setup.py with pyproject.toml (PEP 621) - Add setuptools-scm for automatic versioning from git tags - Add publish.yml workflow for automated PyPI releases via Trusted Publishing - Update tests.yml cache dependency path 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Update all code examples to use new functional API (train, inference_single) - Fix function names (build_snapshot_matrix) - Add JAX-based feature highlight - Add autodifferentiation example section - Use importlib.metadata for dynamic version from setuptools-scm 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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other than the title, thinsg to note here are that the APi has changed to a functional style which is more idiomatic JAX. the motivation for the switch is to enable autodiff. I've added to the examples folder to showcase this.