The Bayesian Neural Kalman Filter uses a trained BNN to predict UAV states and uncertainties, then applies a Kalman update to outperform standard EKF and UKF on synthetic data under high noise and low sampling rates.
Hands-on Bayesian Neural Networks – a Tutorial for Deep Learning Users
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Framework embeds aleatoric and epistemic uncertainties into BNN parameter variances and applies moment propagation for sampling-free variational inference in lightweight networks.
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Neural Aided Kalman Filtering for UAV State Estimation in Degraded Sensing Environments
The Bayesian Neural Kalman Filter uses a trained BNN to predict UAV states and uncertainties, then applies a Kalman update to outperform standard EKF and UKF on synthetic data under high noise and low sampling rates.
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A Framework for Variational Inference of Lightweight Bayesian Neural Networks with Heteroscedastic Uncertainties
Framework embeds aleatoric and epistemic uncertainties into BNN parameter variances and applies moment propagation for sampling-free variational inference in lightweight networks.