# \#forward

**URL:** https://discourse.julialang.org/tag/forward/315.md

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## [Simulation HJM model via stochastic Diffeq](https://discourse.julialang.org/t/simulation-hjm-model-via-stochastic-diffeq/61089)

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**Author:** [@kirgush](https://discourse.julialang.org/u/kirgush)\
**Replies:** 8\
**Last updated:** [January 5, 2023, 10:55pm UTC](https://discourse.julialang.org/t/simulation-hjm-model-via-stochastic-diffeq/61089 "2023-01-05T22:55:08Z")

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I want to do forward curve simulation from simplest HJM model using awesome DiffEq package: using Parameters using Statistics using Printf using Plots using DifferentialEquations α=0.4 σ = 1.4 M = 10 u₀= 10 f(u,p,t) …

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## [Implementation of an implace Hessian of a vector-valued function?](https://discourse.julialang.org/t/implementation-of-an-implace-hessian-of-a-vector-valued-function/33720)

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**Author:** [@longemen3000](https://discourse.julialang.org/u/longemen3000)\
**Replies:** 5\
**Last updated:** [February 1, 2021, 4:45pm UTC](https://discourse.julialang.org/t/implementation-of-an-implace-hessian-of-a-vector-valued-function/33720 "2021-02-01T16:45:05Z")

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HI, i’m looking to implement an implace hessian of a vector-valued function, for example: f(x) = \[x\[1\],x\[2\],sin(x\[1\]),sum(x)\] The ForwardDiff Documentation gives an out of place example (slightly wrong, as size(f(x)) …

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## [Faster way of calculate two-argument ForwardDiff gradient?](https://discourse.julialang.org/t/faster-way-of-calculate-two-argument-forwarddiff-gradient/33948)

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**Author:** [@longemen3000](https://discourse.julialang.org/u/longemen3000)\
**Replies:** 1\
**Last updated:** [January 29, 2020, 8:57pm UTC](https://discourse.julialang.org/t/faster-way-of-calculate-two-argument-forwarddiff-gradient/33948 "2020-01-29T20:57:00Z")

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i have a function f(x1,x2) . sometimes i need dfdx1 , sometimes i need dfdx2, those cases are easy with the existing ForwardDiff API. the problem is when i need the two properties at once. gradient is one way, calling ea…

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## [Matrix Free transpose jacobian using AD](https://discourse.julialang.org/t/matrix-free-transpose-jacobian-using-ad/32511)

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**Author:** [@rveltz](https://discourse.julialang.org/u/rveltz)\
**Replies:** 7\
**Last updated:** [December 20, 2019, 4:35pm UTC](https://discourse.julialang.org/t/matrix-free-transpose-jacobian-using-ad/32511 "2019-12-20T16:35:43Z")

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Hi, I would like to evaluate the transpose of the jacobian of a function F using ForwardDiff.jl or any AD. Is it possible? I read that reverse mode would provide this but failed to achieve this using ReverseDiff.jl. I …