86 citations · 192 across the 27 of their papers we have counts for
4 papers · 1 filter
Robust Learning via Ensemble Density Propagation in Deep Neural Networks
Giuseppina Carannante, Dimah Dera, Ghulam Rasool +2
Learning in uncertain, noisy, or adversarial environments is a challenging task for deep neural networks (DNNs). We propose a new theoretically grounded and efficient approach for…
Scalable Learning With a Structural Recurrent Neural Network for Short-Term Traffic Prediction
Youngjoo Kim, Peng Wang, Lyudmila Mihaylova
This paper presents a scalable deep learning approach for short-term traffic prediction based on historical traffic data in a vehicular road network. Capturing the spatio-temporal…
Variational Bayesian inference of hidden stochastic processes with unknown parameters
Komlan Atitey, Pavel Loskot, Lyudmila Mihaylova
Estimating hidden processes from non-linear noisy observations is particularly difficult when the parameters of these processes are not known. This paper adopts a machine learning…
Structural Recurrent Neural Network for Traffic Speed Prediction
Youngjoo Kim, Peng Wang, Lyudmila Mihaylova
Deep neural networks have recently demonstrated the traffic prediction capability with the time series data obtained by sensors mounted on road segments. However, capturing spatio-…