Results 241 to 250 of about 751,622 (266)

GNN2GNN: Graph neural networks to generate neural networks.

2022
The success of neural networks (NNs) is tightly linked with their architectural design—a complex problem by itself. We here introduce a novel framework leveraging Graph Neural Networks to Generate Neural Networks (GNN2GNN) where powerful NN architectures can be learned out of a set of available architecture-performance pairs.
Andrea Agiollo, Andrea Omicini
openaire   +1 more source

A survey of uncertainty in deep neural networks

Artificial Intelligence Review, 2023
Jianxiang Feng, Xiao Xiang Zhu, Jakob Gawlikowski   +2 more
exaly  

Neural networks

IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 2003
openaire   +2 more sources

The Future of Memristors: Materials Engineering and Neural Networks

Advanced Functional Materials, 2021
Kaixuan Sun, J S Chen, Xiaobing Yan
exaly  

Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks

ACM Computing Surveys, 2022
Claudio Filipi Goncalves Dos Santos, João Paulo Papa   +1 more
exaly  

Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions

Neurocomputing, 2022
Ameya D Jagtap, Yeonjong Shin, Kenji Kawaguchi   +2 more
exaly  

Coherence resonance in neural networks: Theory and experiments

Physics Reports, 2023
Alexander N Pisarchik, Alexander E Hramov   +1 more
exaly  

Neural networks

Microprocessing and Microprogramming, 1993
openaire   +1 more source

Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial

IEEE Communications Surveys and Tutorials, 2019
Mingzhe Chen, Ursula Challita, Walid Saad   +2 more
exaly  

Ensembling neural networks: Many could be better than all

Artificial Intelligence, 2002
Zhi-Hua Zhou, Jianxin Wu
exaly