Daily math problems for you liking and difficulty.

Differentiable generalized eigensolver in JAX. Extracted from PYSCFAD implementation.

A discrete convolution engine for generating exact n-th derivatives of "Log-Towers," A = h(x)·ln(g(x))/ln(f(x)). Features Omega-Kernel (v1.0.0) for O(n^3) polynomial generation, replacing iterative differentiation with cached sector decomposition.

Programming language for symbolic computation with unusual combination of pattern matching features: Tree patterns, associative patterns and expressions embedded in patterns.

clad -- automatic differentiation for C/C++

An interface to various automatic differentiation backends in Julia.

Numerical derivatives for Python

Single cell trajectory detection

Open-source cross-platform symbolic algebra library for C# and F#. Can be used for both production and research purposes.

Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.

This is a technical document about physics, explaining fundamental kinematics concepts with calculus-based algebraic derivations. Occasional Python scripts are included for verification and justification of assumptions and derivations made in the explanatory sections.

xFunc provides a powerful parser and analyzer for mathematical expressions. It excels at calculating derivatives, simplifying expressions, and achieving high performance.

Automatic Differentiation with C++

Example scripts and notebooks showcasing how to use DerivKit’s tools for analysis, differentiation, and forecasting.

A symbolic integration calculator built from scratch (no CAS libraries for the core). UI and secondary utilities may use libraries, but the integration engine, parser, AST, simplifier, differentiation, and rule system are handwritten.

Fortran library providing automatic differentiation

Optimal numerical differentiation of noisy time series data in python.

MultiPrecision Numerical Differentiation Implements

Double-Double Numerical Differentiation Implements

Example workflow of PCA-based method of comparing and visualizing differentiation progression (timing) between two groups of samples in bulk RNA-seq data. Specifically, this method allows the user to define the differentiation 'start' and 'end' points, which is helpful if the timing difference between groups occurs between specific timepoints.