Vehicle-to-Everything (V2X) Datasets for Machine Learning-Based Predictive Quality of Service
Author:
Affiliation:
1. University of Bologna, & WiLab,CNIT,Italy
2. Politecnico di Milano,Italy
3. Huawei Technologies, Duesseldorf GmbH,Munich Research Center,Germany
4. University of Technology,Czech Republic
5. University of Oulu,Finland
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Computer Science Applications
Link
http://xplorestaging.ieee.org/ielx7/35/10268118/10268872.pdf?arnumber=10268872
Reference15 articles.
1. A Theoretically Grounded Application of Dropout in Recurrent Neural Networks;gal;Advances in neural information processing systems,2016
2. Weight Uncertainty in Neural Network;blundell;Proc IEEE Intern Conf on Machine Learning,0
3. A Survey of Deep Active Learning;ren;ACM Comput Surv,2021
4. Hands-On Bayesian Neural Networks—A Tutorial for Deep Learning Users
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