Robust Decision-Making in the Internet of Battlefield Things Using Bayesian Neural Networks-Reference-Cited by-同舟云学术

Robust Decision-Making in the Internet of Battlefield Things Using Bayesian Neural Networks

Published:2021-12-12 Issue: Volume: Page:
ISSN:
Container-title:2021 Winter Simulation Conference (WSC)
language:
Short-container-title:

Author:

Cobb Adam D.¹,Jalaian Brian A.¹,Bastian Nathaniel D.²,Russell Stephen¹

Affiliation:

1. U.S. Army Futures Command,CCDC DEVCOM Army Research Laboratory,Adelphi,MD,USA,20783

2. Army Cyber Institute, United States Military Academy,West Point,NY,USA,10996

Funder

U.S. Army Combat Capabilities Development Command (DEVCOM)

Army Research Laboratory

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9715283/9715284/09715532.pdf?arnumber=9715532

Reference33 articles.

1. Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning;zhang;ICLRE,2020

2. Bayesian learning via stochastic gradient Langevin dynamics;welling;Proceedings of the 28th International Conference on Machine Learning (ICML-11),2011

3. URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks;vadera;ArXiv Preprint,2020

4. Parallel Distributed Processing

5. Practical variational inference for neural networks;graves;Advances in neural information processing systems,2011

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. FreqMAE: Frequency-Aware Masked Autoencoder for Multi-Modal IoT Sensing;Proceedings of the ACM Web Conference 2024;2024-05-13

2. Uncertainty-Quantified, Robust Deep Learning for Network Intrusion Detection;2023 Winter Simulation Conference (WSC);2023-12-10

3. Data-efficient, federated learning for raw network traffic detection;Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V;2023-06-12

4. Transfer learning for raw network traffic detection;Expert Systems with Applications;2023-01

5. Self-Supervised Learning from Unlabeled IoT Data;Artificial Intelligence for Edge Computing;2023