auto-differentiation/xad
Fast, easy automatic differentiation in C++
Repository profile
High-Performance Automatic Differentiation for Python
Tracked growth, recent movement, and commit velocity from stored repository snapshots.
Latest capture 2026-06-19 22:39
1 capture since 2026-06-19
Stars from baseline 0
All tracked data
Frameworks, package managers, ecosystems, and dependency manifests found during catalog scans.
Scanned 2026-06-19 22:39
CMakeLists.txt
c-cpp ecosystem,
0 dependencies
pyproject.toml
python ecosystem,
11 dependencies
poetry.lock
python ecosystem,
30 dependencies
src/CMakeLists.txt
c-cpp ecosystem,
1 dependency
Searchable topics, generated tags, and stack labels that explain where this repository fits.
Agent instructions and tool configuration paths found in the repository tree.
Nearest indexed repositories by embedding similarity.
Fast, easy automatic differentiation in C++
QuantLib with AAD
Fast Risks with QuantLib in Python
Efficiently computes derivatives of NumPy code.
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/