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ORCIDFearghal O'Donncha
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2020 – today
- 2024
[i9]Nianjun Zhou, Dhaval Patel, Shuxin Lin, Fearghal O'Donncha:
Towards Automated Solution Recipe Generation for Industrial Asset Management with LLM. CoRR abs/2407.18992 (2024)- 2023
- [c3]Amadou Ba, Fearghal O'Donncha, Joern Ploennigs, Muneeza Azmat:
Efficient Extraction of Insights at the Edges of Distributed Systems. IEEE Big Data 2023: 1610-1619 - [c2]Muneeza Azmat, Malvern Madondo
, Arun Bawa, Kelsey Dipietro, Raya Horesh, Michael Jacobs, Raghavan Srinivasan, Fearghal O'Donncha:
Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management. IJCAI 2023: 5897-5905 - [i8]Malvern Madondo, Muneeza Azmat, Kelsey Dipietro, Raya Horesh, Michael Jacobs, Arun Bawa, Raghavan Srinivasan, Fearghal O'Donncha:
A SWAT-based Reinforcement Learning Framework for Crop Management. CoRR abs/2302.04988 (2023) - [i7]Roland Oruche, Fearghal O'Donncha:
Attention-based Domain Adaptation Forecasting of Streamflow in Data Sparse Regions. CoRR abs/2302.05386 (2023) - [i6]Abigail Langbridge, Fearghal O'Donncha, Amadou Ba, Fabio Lorenzi, Christopher Lohse, Joern Ploennigs:
Causal Temporal Graph Convolutional Neural Networks (CTGCN). CoRR abs/2303.09634 (2023) - 2022
- [j6]Fearghal O'Donncha, Yihao Hu, Paulito Palmes, Meredith Burke, Ramón Filgueira, Jon Grant:
A spatio-temporal LSTM model to forecast across multiple temporal and spatial scales. Ecol. Informatics 69: 101687 (2022) - [i5]Muneeza Azmat, Malvern Madondo, Kelsey Dipietro, Raya Horesh, Arun Bawa, Michael Jacobs, Raghavan Srinivasan, Fearghal O'Donncha:
Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management. CoRR abs/2212.06565 (2022) - 2021
- [c1]Fearghal O'Donncha, Albert Akhriev, Bradley Eck, Meredith Burke, Ramón Filgueira, Jon Grant:
Deployment and Management of Time Series Forecasts in Ocean Industry. IEEE BigData 2021: 4091-4096 - [i4]Yihao Hu, Fearghal O'Donncha, Paulito Palmes, Meredith Burke, Ramón Filgueira, Jon Grant:
A spatio-temporal LSTM model to forecast across multiple temporal and spatial scales. CoRR abs/2108.11875 (2021) - [i3]Roland Oruche, Lisa Egede, Tracy Baker, Fearghal O'Donncha:
Transfer learning to improve streamflow forecasts in data sparse regions. CoRR abs/2112.03088 (2021) - 2020
- [j5]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:
AllScale toolchain pilot applications: PDE based solvers using a parallel development environment. Comput. Phys. Commun. 251: 107089 (2020) - [j4]Philipp Haehnel, Jakub Marecek, Julien Monteil, Fearghal O'Donncha:
Using deep learning to extend the range of air pollution monitoring and forecasting. J. Comput. Phys. 408: 109278 (2020)
2010 – 2019
- 2019
- [j3]Fearghal O'Donncha, Jon Grant:
Precision Aquaculture. IEEE Internet Things Mag. 2(4): 26-30 (2019) - [j2]Emanuele Ragnoli, Mykhaylo Zayats, Fearghal O'Donncha, Sergiy Zhuk:
Localised sequential state estimation for advection dominated flows with non-Gaussian uncertainty description. J. Comput. Phys. 387: 356-375 (2019) - [i2]Stefan Wolff, Fearghal O'Donncha, Bei Chen:
Statistical and machine learning ensemble modelling to forecast sea surface temperature. CoRR abs/1909.08573 (2019) - 2018
- [i1]Philipp Haehnel, Jakub Marecek, Julien Monteil, Fearghal O'Donncha:
Scaling up Deep Learning for PDE-based Models. CoRR abs/1810.09425 (2018) - 2014
- [j1]Fearghal O'Donncha, Emanuele Ragnoli, Frank Suits:
Parallelisation study of a three-dimensional environmental flow model. Comput. Geosci. 64: 96-103 (2014)
Coauthor Index
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