Extreme summer precipitation events in China have grown increasingly frequent and intense, posing severe threats to human life, property, and ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...

Traditional path planning algorithms often face problems such as local optimum traps and low monitoring efficiency in agricultural UAV operations, making it difficult to meet the operational ...

We derive and implement a second-order adjoint method to compute exact gradients and Hessians for a prototypical quantum optimal control problem, that of solving for the minimal energy applied ...

Just wanted to ask if I have the right understanding of what algorithms are being used for each adjoint method, as the documentation does not link each method to a paper or reference.

Hi, I tried to use the following code to test the effects of using adjoint method import torch import torch.nn as nn from torchdiffeq import odeint_adjoint as odeint import time class ...

Abstract: We outline the derivation and illustrate the application of adjoint equations to the problem of determining the effects of small changes of various design parameters on the output power and ...