PyPI page
Home page
Author:
None
Summary:
Domain-agnostic differentiable-inversion primitives for MIDAS: gradient fitting, scale-invariant losses, Laplace uncertainty, Fisher-information experiment design, mixture deconvolution, and amortised-inference surrogates.
Latest version:
0.1.0
Required dependencies:
numpy
|
torch
Optional dependencies:
pytest
Downloads last day:
2
Downloads last week:
10
Downloads last month:
49