1 citations · 3 across the 7 of their papers we have counts for
7 papers
Heteroscedastic Neural Networks for Path Loss Prediction with Link-Specific Uncertainty
Jonathan Ethier
Traditional and modern machine learning-based path loss models typically assume a constant prediction variance. We propose a neural network that jointly predicts the mean and link-…
Reciprocity-Aware Convolutional Neural Networks for Map-Based Path Loss Prediction
Ryan G. Dempsey, Jonathan Ethier, Halim Yanikomeroglu
Path loss modeling is a widely used technique for estimating point-to-point losses along a communications link from transmitter (Tx) to receiver (Rx). Accurate path loss prediction…
Uncertainty Estimation for Path Loss and Radio Metric Models
Alexis Bose, Jonathan Ethier, Ryan G. Dempsey +1
This research leverages Conformal Prediction (CP) in the form of Conformal Predictive Systems (CPS) to accurately estimate uncertainty in a suite of machine learning (ML)-based rad…
Environmental Feature Engineering and Statistical Validation for ML-Based Path Loss Prediction
Jonathan Ethier, Mathieu Chateauvert, Ryan G. Dempsey +1
Wireless communications rely on path loss modeling, which is most effective when it includes the physical details of the propagation environment. Acquiring this data has historical…
Investigating Map-Based Path Loss Models: A Study of Feature Representations in Convolutional Neural Networks
Ryan G. Dempsey, Jonathan Ethier, Halim Yanikomeroglu
Path loss prediction is a beneficial tool for efficient use of the radio frequency spectrum. Building on prior research on high-resolution map-based path loss models, this paper st…
Target Strangeness: A Novel Conformal Prediction Difficulty Estimator
Alexis Bose, Jonathan Ethier, Paul Guinand
This paper introduces Target Strangeness, a novel difficulty estimator for conformal prediction (CP) that offers an alternative approach for normalizing prediction intervals (PIs).…
Conformal Prediction for Multimodal Regression
Alexis Bose, Jonathan Ethier, Paul Guinand
This paper introduces multimodal conformal regression. Traditionally confined to scenarios with solely numerical input features, conformal prediction is now extended to multimodal…