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Your step-by-step guide — create deponent formula
Using airSlate SignNow’s eSignature any business can speed up signature workflows and eSign in real-time, delivering a better experience to customers and employees. create deponent formula in a few simple steps. Our mobile-first apps make working on the go possible, even while offline! Sign documents from anywhere in the world and close deals faster.
Follow the step-by-step guide to create deponent formula:
- Log in to your airSlate SignNow account.
- Locate your document in your folders or upload a new one.
- Open the document and make edits using the Tools menu.
- Drag & drop fillable fields, add text and sign it.
- Add multiple signers using their emails and set the signing order.
- Specify which recipients will get an executed copy.
- Use Advanced Options to limit access to the record and set an expiration date.
- Click Save and Close when completed.
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Edit initials deponent
hi thank you so much for watching my name is diego and today we will review how to implement a physics inform deponetti python as always this code will be available in my github and the link will be in the description of this video here you will find a few more examples that could be useful to you if you're just starting in this field we use zip on it to approximate operators but what's exactly an operator and to answer that question let's go back to what's a function well a function it's a mathematical structure that maps between vector spaces for example uh the let's take the sine of x if we input any real number we will get a number between 0 and 1. in other words a function takes a number and outputs another number on the other hand an operator maps between infinite dimensional function spaces for example let's take the derivative operator and let's apply it to the same function the sine of x if we apply the derivative operator to the sine of x well the answer the output would be a function that would be the cosine of x in other words an operator takes a function and transforms it into another function but what do we want to study operators to answer that question let's go back to one of the previous tutorials where we solved the burgers equation using a physics informed neural network we are giving the diffusion coefficient the domain and the initial and boundary conditions but what if we want to change the fluid well then the diffusion coefficient will change which would mean that we are essentially in a different problem so we need another neural network but wait what if we just want to change the domain a little bit well it would be a different problem and we need another network so is there a way to solve the broker's equation in a general way i mean where some parameters can change and i can still get the solution without the need of repeating the whole process and the answer would be yes and that's where operators come really handy so let's recall that in a pde we usually have an input function and that the solution of the pde is also a function so we could get an operator that takes the input function and now puts the solution of that partial differential equation and that's basically what a deponent is meant to do we know we want operators to solve pdes in a general way or in other words we need operators to solve parametric pds but how to get those operators well for that we have the universal approximation theorem for operators here let's pay attention to this g of u of y if we observe at the output of an operator it's a function in this case g of u and if we evaluate a function at any point...
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