71 citations · 72 across the 5 of their papers we have counts for
5 papers
Improving Variational Autoencoder using Random Fourier Transformation: An Aviation Safety Anomaly Detection Case-Study
Ata Akbari Asanjan, Milad Memarzadeh, Bryan Matthews +1
In this study, we focus on the training process and inference improvements of deep neural networks (DNNs), specifically Autoencoders (AEs) and Variational Autoencoders (VAEs), usin…
Deep Transfer Learning on Satellite Imagery Improves Air Quality Estimates in Developing Nations
Nishant Yadav, Meytar Sorek-Hamer, Michael Von Pohle +9
Urban air pollution is a public health challenge in low- and middle-income countries (LMICs). However, LMICs lack adequate air quality (AQ) monitoring infrastructure. A persistent…
ExoMiner: A Highly Accurate and Explainable Deep Learning Classifier that Validates 301 New Exoplanets
Hamed Valizadegan, Miguel Martinho, Laurent S. Wilkens +10
The kepler and TESS missions have generated over 100,000 potential transit signals that must be processed in order to create a catalog of planet candidates. During the last few yea…
Better Boosting with Bandits for Online Learning
Nikolaos Nikolaou, Joseph Mellor, Nikunj C. Oza +1
Probability estimates generated by boosting ensembles are poorly calibrated because of the margin maximization nature of the algorithm. The outputs of the ensemble need to be prope…
Semi-Markov Switching Vector Autoregressive Model-based Anomaly Detection in Aviation Systems
Igor Melnyk, Arindam Banerjee, Bryan Matthews +1
In this work we consider the problem of anomaly detection in heterogeneous, multivariate, variable-length time series datasets. Our focus is on the aviation safety domain, where da…