614 citations · 721 across the 13 of their papers we have counts for
14 papers
Robust Classification of High-Dimensional Spectroscopy Data Using Deep Learning and Data Synthesis
James Houston, Frank G. Glavin, Michael G. Madden
This paper presents a new approach to classification of high dimensional spectroscopy data and demonstrates that it outperforms other current state-of-the art approaches. The speci…
Graph Convolutional Networks: analysis, improvements and results
Ihsan Ullah, Mario Manzo, Mitul Shah +1
In the current era of neural networks and big data, higher dimensional data is processed for automation of different application areas. Graphs represent a complex data organization…
Dealing with Stochasticity in Biological ODE Models
Hamda Ajmal, Michael Madden, Catherine Enright
Mathematical modeling with Ordinary Differential Equations (ODEs) has proven to be extremely successful in a variety of fields, including biology. However, these models are complet…
PROFET: Construction and Inference of DBNs Based on Mathematical Models
Hamda Ajmal, Michael Madden, Catherine Enright
This paper presents, evaluates, and discusses a new software tool to automatically build Dynamic Bayesian Networks (DBNs) from ordinary differential equations (ODEs) entered by the…
A Virtual Testbed for Critical Incident Investigation with Autonomous Remote Aerial Vehicle Surveying, Artificial Intelligence, and Decision Support
David L. Smyth, Sai Abinesh, Nazli B. Karimi +4
Autonomous robotics and artificial intelligence techniques can be used to support human personnel in the event of critical incidents. These incidents can pose great danger to human…
Using a Game Engine to Simulate Critical Incidents and Data Collection by Autonomous Drones
David L. Smyth, Frank G. Glavin, Michael G. Madden
Using a game engine, we have developed a virtual environment which models important aspects of critical incident scenarios. We focused on modelling phenomena relating to the identi…