George De Ath

Orcid: 0000-0003-4909-0257

Affiliations:
  • University of Exeter, Exeter, Devon, UK


According to our database1, George De Ath authored at least 22 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Graph-based Complexity Forecasts in UK En Route Airspace Using Relevant Aircraft Interactions.
CoRR, May, 2026

Human-in-the-Loop Testing of AI Agents for Air Traffic Control with a Regulated Assessment Framework.
CoRR, January, 2026

Online Action-Stacking Improves Reinforcement Learning Performance for Air Traffic Control.
CoRR, January, 2026

A Future Capabilities Agent for Tactical Air Traffic Control.
CoRR, January, 2026

A Probabilistic Digital Twin of UK En Route Airspace for Training and Evaluating AI Agents for Air Traffic Control.
CoRR, January, 2026

2025
AirTrafficGen: Configurable Air Traffic Scenario Generation with Large Language Models.
CoRR, August, 2025

Air Traffic Controller Task Demand via Graph Neural Networks: An Interpretable Approach to Airspace Complexity.
CoRR, July, 2025

BEACON: Continuous Bi-objective Benchmark problems with Explicit Adjustable COrrelatioN control.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2025

2024
Is greed still good in multi-objective Bayesian optimisation?
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2023
Context-Aware Generative Models for Prediction of Aircraft Ground Tracks.
CoRR, 2023

2022
A Probabilistic Model for Aircraft in Climb using Monotonic Functional Gaussian Process Emulators.
CoRR, 2022

MBORE: multi-objective Bayesian optimisation by density-ratio estimation.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

2021
Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation.
ACM Trans. Evol. Learn. Optim., 2021

Asynchronous ε-Greedy Bayesian Optimisation.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

How Bayesian should Bayesian optimisation be?
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020
What do you mean?: the role of the mean function in bayesian optimisation.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

ϵ-shotgun: ϵ-greedy batch bayesian optimisation.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019
Object tracking in video with part-based tracking by feature sampling.
PhD thesis, 2019

The Seventh Visual Object Tracking VOT2019 Challenge Results.
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Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018
Part-Based Tracking by Sampling.
CoRR, 2018

The Sixth Visual Object Tracking VOT2018 Challenge Results.
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Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Visual Object Tracking: The Initialisation Problem.
Proceedings of the 15th Conference on Computer and Robot Vision, 2018


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