A. Durrant

发表

How might technology rise to the challenge of data sharing in agri-food?

David May, A. Durrant, Milan Markovic, 2021, Global Food Security.

Machine learning for analysis of real nuclear plant data in the frequency domain Annals of Nuclear Energy

S. Kollias, C. Demazière, P. Vinai, 2022 .

Machine learning for analysis of real nuclear plant data in the frequency domain

S. Kollias, C. Demazière, P. Vinai, 2022, Annals of Nuclear Energy.

Deep learning techniques for in-core perturbation identification and localization of time-series nuclear plant measurements

S. Kollias, A. Stafylopatis, A. Durrant, 2022, Annals of Nuclear Energy.

Hyperspherically regularized networks for self-supervision Image and Vision Computing

A. Durrant, G. Leontidis, 2022 .

Decarbonising our food systems: contextualising digitalisation for net zero

L. Manning, C. Jabbour, R. Maull, 2023, Frontiers in Sustainable Food Systems.

NEUTRON NOISE-BASED ANOMALY CLASSIFICATION AND LOCALIZATION USING MACHINE LEARNING

Antonios Mylonakis, Paolo Vinai, Christophe Demaziere, 2020, EPJ Web of Conferences.

HMSN: Hyperbolic Self-Supervised Learning by Clustering with Ideal Prototypes

A. Durrant, G. Leontidis, 2023, ArXiv.

S-JEA: Stacked Joint Embedding Architectures for Self-Supervised Visual Representation Learning

A. Durrant, G. Leontidis, Alvzbveta Manov'a, 2023, ArXiv.

S-JEA: S TACKED J OINT E MBEDDING A RCHITECTURES FOR S ELF -S UPERVISED V ISUAL R EPRESENTATION L EARNING

A. Durrant, G. Leontidis, Alžběta Manová, 2023 .

3D convolutional and recurrent neural networks for reactor perturbation unfolding and anomaly detection

A. DURRANT, G. LEONTIDIS, S. KOLLIAS, 2019, EPJ Nuclear Sciences & Technologies.

Hyperspherically regularized networks for self-supervision

A. Durrant, G. Leontidis, 2021, Image Vis. Comput..

3D convolutional and recurrent neural networks for reactor perturbation unfolding and anomaly detection

S. Kollias, G. Leontidis, A. Durrant, 2019, EPJ Nuclear Sciences & Technologies.