Optimizing Multidimensional Pooling for Variational Quantum Algorithms

Optimizing Multidimensional Pooling for Variational Quantum Algorithms

Convolutional neural networks (CNNs) have proven to be a very efficient class of machine learning (ML) architectures for handling multidimensional data by maintaining data locality, especially in the field of computer vision. Data pooling, a major component of CNNs, plays a crucial role in extractin...

Full description

Bibliographic Details
Main Authors: Mingyoung Jeng, Alvir Nobel, Vinayak Jha, David Levy, Dylan Kneidel, Manu Chaudhary, Ishraq Islam, Evan Baumgartner, Eade Vanderhoof, Audrey Facer, Manish Singh, Abina Arshad, Esam El-Araby
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Algorithms
Subjects:
quantum computing
convolutional neural networks
quantum machine learning
pooling layers
Online Access:https://www.mdpi.com/1999-4893/17/2/82

Internet

https://www.mdpi.com/1999-4893/17/2/82

Similar Items