A modernisation of the SLATEC library
📏 Monotonic cubic interpolation in Julia
Yield curve interpolation, parametric fitting (Nelson-Siegel, Svensson, PCHIP), compounding, and bond pricing — zero-dependency Rust
WarpPCHIP-Net integrates RNN memory, convolutional extraction, and PCHIP warping for O(N) long-sequence modeling via serial token processing. Core innovations: non-uniform PCHIP memory (sparse distant for compression, dense recent for detail) and learnable sampling grid. Ideal for language modeling and time-series forecasting.
Python workflow for PCHIP-based MGI and FBRM onset analysis, including review galleries and a synthetic example.
Command-line tools for data processing, smoothing, and visualization in scientific workflows.
A shape-preserving monotone cubic interpolation library with derivatives, analytic integration and plateau-aware inverse brackets. Explicit domains, tolerances and iteration limits make synthetic calibration curves checkable without charts.
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