Daniel Cunnington

According to our database, Daniel Cunnington authored at least 19 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Can we Constrain Concept Bottleneck Models to Learn Semantically Meaningful Input Features?

Jack Furby, Daniel Cunnington, Dave Braines, Alun D. Preece

CoRR, 2024

The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning.

Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra Russo

Proceedings of the Neural-Symbolic Learning and Reasoning - 18th International Conference, 2024

2023

FFNSL: Feed-Forward Neural-Symbolic Learner.

Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra Russo

Mach. Learn., February, 2023

Cybersecurity in Motion: A Survey of Challenges and Requirements for Future Test Facilities of CAVs.

Ioannis Mavromatis, Theodoros Spyridopoulos, Pietro Edoardo Carnelli, Woon Hau Chin, Ahmed Khalil, Jennifer Chakravarty, Lucia Cipolina Kun, Robert J. Piechocki, Colin Robbins, Daniel Cunnington, Leigh Chase, Lamogha Chiazor, Chris Preston, Rahul, Aftab Khan

CoRR, 2023

Symbolic Learning for Material Discovery.

Daniel Cunnington, Flaviu Cipcigan, Rodrigo Neumann Barros Ferreira, Jonathan Booth

CoRR, 2023

Towards a Deeper Understanding of Concept Bottleneck Models Through End-to-End Explanation.

Jack Furby, Daniel Cunnington, Dave Braines, Alun D. Preece

CoRR, 2023

Neuro-Symbolic Learning of Answer Set Programs from Raw Data.

Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra Russo

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2021

FF-NSL: Feed-Forward Neural-Symbolic Learner.

Daniel Cunnington, Mark Law, Alessandra Russo, Jorge Lobo

CoRR, 2021

Towards Neural-Symbolic Learning to support Human-Agent Operations.

Daniel Cunnington, Mark Law, Alessandra Russo, Jorge Lobo, Lance M. Kaplan

Proceedings of the 24th IEEE International Conference on Information Fusion, 2021

Inductive Learning of Complex Knowledge from Raw Data.

Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra Russo

Proceedings of the Thinking Fast and Slow and Other Cognitive Theories in AI, 2021

2020

NSL: Hybrid Interpretable Learning From Noisy Raw Data.

Daniel Cunnington, Alessandra Russo, Mark Law, Jorge Lobo, Lance M. Kaplan

CoRR, 2020

2019

Synthetic Ground Truth Generation for Evaluating Generative Policy Models.

Daniel Cunnington, Graham White, Geeth de Mel

CoRR, 2019

A Demonstration of Generative Policy Models in Coalition Environments.

Daniel Cunnington, Graham White, Mark Law, Geeth de Mel

Proceedings of the Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection, 2019

A Generative Policy Model for Connected and Autonomous Vehicles.

Daniel Cunnington, Irene Manotas, Mark Law, Geeth de Mel, Seraphin B. Calo, Elisa Bertino, Alessandra Russo

Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019

A Comparison Between Statistical and Symbolic Learning Approaches for Generative Policy Models.

Graham White, Daniel Cunnington, Mark Law, Elisa Bertino, Geeth de Mel, Alessandra Russo

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Generative Policies for Coalition Systems - A Symbolic Learning Framework.

Elisa Bertino, Graham White, Jorge Lobo, John Ingham, Gregory H. Cirincione, Alessandra Russo, Mark Law, Seraphin B. Calo, Irene Manotas, Dinesh C. Verma, Amani Abu Jabal, Daniel Cunnington, Geeth de Mel

Proceedings of the 39th IEEE International Conference on Distributed Computing Systems, 2019

Towards a Neural-Symbolic Generative Policy Model.

Daniel Cunnington, Mark Law, Alessandra Russo, Elisa Bertino, Seraphin B. Calo

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Reduce Cognitive Burden on Drivers through Contextualising Environments.

Daniel Cunnington, Geeth de Mel, Darren Shaw

Proceedings of the 87th IEEE Vehicular Technology Conference, 2018

AGENP: An ASGrammar-based GENerative Policy Framework.

Seraphin B. Calo, Irene Manotas, Geeth de Mel, Daniel Cunnington, Mark Law, Dinesh C. Verma, Alessandra Russo, Elisa Bertino

Proceedings of the Policy-Based Autonomic Data Governance [extended papers from the Second International Workshop on Policy-based Autonomic Data Governance, 2018