In this paper, adjoint gradient and Hessian operators are introduced into the calculation of FWI objective function to improve the inversion accuracy. Firstly, the adjoint gradient method is used to ...

It basically works for finding the local minima of any differential function ... the calculation of the prediction and updated value of the parameter until the convergence. Let’s check how we can ...

These computational graphs can be exported as pure Python functions ... Faster Genetic Programming based on Local Gradient Search of Numeric Leaf Values. In Proceedings of the Genetic and Evolutionary ...

Abstract: This article proposes a distributed algorithm for a network of agents to solve an optimization problem with separable objective function and locally ... shows that the distributed ...

In this work, we showcase SGTPy, a Python open ... For the computation of interfacial properties, SGTPy incorporates several options to solve the interfacial concentration, such as the path technique, ...

Abstract: In this letter, we propose a bio-inspired derivative-free optimization algorithm capable of minimizing objective ... not require explicit gradient computation or estimation and is shown in ...

I have a function to calculate gradient ... the total calculation speed is the same with on one GPU. I think it used two GPUs one by one. I want to use two GPUs synchronosly, what method can I use?