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docs: add scipy least squares API docs #645

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2 changes: 2 additions & 0 deletions docs/api.rst
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Expand Up @@ -98,6 +98,8 @@ Nonlinear least squares

jaxopt.GaussNewton
jaxopt.LevenbergMarquardt
jaxopt.ScipyLeastSquares
jaxopt.ScipyBoundedLeastSquares

Root finding
------------
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14 changes: 14 additions & 0 deletions docs/nonlinear_least_squares.rst
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Expand Up @@ -98,3 +98,17 @@ parameters:

where :math:`\mathbf{J}` is the Jacobian of the residual function w.r.t.
parameters and :math:`\mu` is the damping parameter.

SciPy wrappers
--------------

.. autosummary::
:toctree: _autosummary

jaxopt.ScipyLeastSquares
jaxopt.ScipyBoundedLeastSquares

For users who need SciPy's ``least_squares`` implementation with PyTree and
implicit differentiation support, :class:`jaxopt.ScipyLeastSquares` wraps
unconstrained nonlinear least squares problems and
:class:`jaxopt.ScipyBoundedLeastSquares` handles problems with box constraints.