> A (future) extension of this app is the optimisation of functions which cannnot be writted as mathematical expressions (such as a PDE model) by using user-inp

> A (future) extension of this app is the optimisation of functions which cannnot be writted as mathematical expressions (such as a PDE model) by using user-input values of some points of the function to optimise. If this is particularly interesting to you don't hesitate to send a mail. This is an interesting venue, but how would you go about this without solving the PDE model, itself? I work in a similar area of manifold learning, where our objective is a functional of a solution to a PDE (which is, in some sense, a generalization of that idea), but there seems to be no obvious way of optimizing this program without solving for at least the eigenfunctions of the PDE. I'd be curious to hear what the author has in mind. Additionally, I'm also curious as to what algorithms are being used; derivative-free (incl. subgradient-free) methods are usually quite sub-optimal for most classes of problems that I know of, but I'm not sure what the intended audience is, here, so perhaps this would perform quite well in those cases? Anyways, I'd love to test it! But I think HN gave the page the hug-of-death so it's giving me an error...