Bayesian Deep Neural Networks for Supervised Learning of Single-View Depth
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3142915
Abstract: Uncertainty quantification is essential for robotic perception, as overconfident or point estimators can lead to collisions and damages to the environment and the robot. In this letter, we evaluate scalable approaches to uncertainty quantification in… read more here.
Keywords: single view; deep neural; neural networks; depth ... See more keywords
Bayesian Reinforcement Learning and Bayesian Deep Learning for Blockchains With Mobile Edge Computing
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Cognitive Communications and Networking"
DOI: 10.1109/tccn.2020.2994366
Abstract: We present a novel game-theoretic, Bayesian reinforce-ment learning (RL) and deep learning (DL) framework to represent interactions of miners in public and consortium blockchains with mobile edge computing (MEC). Within the framework, we formulate a… read more here.
Keywords: bayesian deep; blockchains mobile; learning; edge computing ... See more keywords
A Bayesian Deep Learning RUL Framework Integrating Epistemic and Aleatoric Uncertainties
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Industrial Electronics"
DOI: 10.1109/tie.2020.3009593
Abstract: Recent years have witnessed the prominent advancements of deep learning (DL) in the arsenal of prognostics and health management. However, the prognostic uncertainty problem extensively existed in industrial devices is not addressed by most DL… read more here.
Keywords: bayesian deep; uncertainty; learning rul; framework ... See more keywords