Fearghal O'Donncha

According to our database, Fearghal O'Donncha authored at least 16 papers between 2014 and 2024.

Collaborative distances:

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

2024

Towards Automated Solution Recipe Generation for Industrial Asset Management with LLM.

Nianjun Zhou, Dhaval Patel, Shuxin Lin, Fearghal O'Donncha

CoRR, 2024

2023

Causal Temporal Graph Convolutional Neural Networks (CTGCN).

Abigail Langbridge, Fearghal O'Donncha, Amadou Ba, Fabio Lorenzi, Christopher Lohse, Joern Ploennigs

CoRR, 2023

Attention-based Domain Adaptation Forecasting of Streamflow in Data Sparse Regions.

Roland Oruche, Fearghal O'Donncha

CoRR, 2023

A SWAT-based Reinforcement Learning Framework for Crop Management.

Malvern Madondo, Muneeza Azmat, Kelsey Dipietro, Raya Horesh, Michael Jacobs, Arun Bawa, Raghavan Srinivasan, Fearghal O'Donncha

CoRR, 2023

Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management.

Muneeza Azmat, Malvern Madondo, Arun Bawa, Kelsey Dipietro, Raya Horesh, Michael Jacobs, Raghavan Srinivasan, Fearghal O'Donncha

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

Efficient Extraction of Insights at the Edges of Distributed Systems.

Amadou Ba, Fearghal O'Donncha, Joern Ploennigs, Muneeza Azmat

Proceedings of the IEEE International Conference on Big Data, 2023

2022

A spatio-temporal LSTM model to forecast across multiple temporal and spatial scales.

Fearghal O'Donncha, Yihao Hu, Paulito Palmes, Meredith Burke, Ramón Filgueira, Jon Grant

Ecol. Informatics, 2022

2021

Transfer learning to improve streamflow forecasts in data sparse regions.

Roland Oruche, Lisa Egede, Tracy Baker, Fearghal O'Donncha

CoRR, 2021

Deployment and Management of Time Series Forecasts in Ocean Industry.

Fearghal O'Donncha, Albert Akhriev, Bradley Eck, Meredith Burke, Ramón Filgueira, Jon Grant

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Using deep learning to extend the range of air pollution monitoring and forecasting.

Philipp Haehnel, Jakub Marecek, Julien Monteil, Fearghal O'Donncha

J. Comput. Phys., 2020

AllScale toolchain pilot applications: PDE based solvers using a parallel development environment.

Fearghal O'Donncha, Roman Iakymchuk, Albert Akhriev, Philipp Gschwandtner, Peter Thoman, Thomas Heller, Xavier Aguilar, Kiril Dichev, Charles Gillan, Stefano Markidis, Erwin Laure, Emanuele Ragnoli, Vassilis Vassiliadis, Michael A. Johnston, Herbert Jordan, Thomas Fahringer

Comput. Phys. Commun., 2020

2019

Localised sequential state estimation for advection dominated flows with non-Gaussian uncertainty description.

Emanuele Ragnoli, Mykhaylo Zayats, Fearghal O'Donncha, Sergiy Zhuk

J. Comput. Phys., 2019

Precision Aquaculture.

Fearghal O'Donncha, Jon Grant

IEEE Internet Things Mag., 2019

Statistical and machine learning ensemble modelling to forecast sea surface temperature.

Stefan Wolff, Fearghal O'Donncha, Bei Chen

CoRR, 2019

2018

Scaling up Deep Learning for PDE-based Models.

Philipp Haehnel, Jakub Marecek, Julien Monteil, Fearghal O'Donncha

CoRR, 2018

2014

Parallelisation study of a three-dimensional environmental flow model.

Fearghal O'Donncha, Emanuele Ragnoli, Frank Suits

Comput. Geosci., 2014