ForwardModeJVP

class probnum.diffeq.odefilter.init_routines.ForwardModeJVP

Bases: _AutoDiffBase

Initialization via Jacobian-vector-product-based automatic differentiation.

Attributes Summary

is_exact	Exactness of the computed initial values.
requires_jax	Whether the implementation of the routine relies on JAX.

Methods Summary

__call__(*, ivp, prior_process)

Call self as a function.

Attributes Documentation

is_exact

Exactness of the computed initial values.

Some initialization routines yield the exact initial derivatives, some others only yield approximations.

requires_jax

Whether the implementation of the routine relies on JAX.

Methods Documentation

__call__(*, ivp, prior_process)

Call self as a function.

Parameters:

• ivp (InitialValueProblem) –

• prior_process (MarkovProcess) –

Return type:

RandomVariable