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Fearghal 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
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
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
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
AllScale toolchain pilot applications: PDE based solvers using a parallel development environment. Comput. Phys. Commun. 251: 107089 (2020) - [j4]Philipp Haehnel
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
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
Parallelisation study of a three-dimensional environmental flow model. Comput. Geosci. 64: 96-103 (2014)
Coauthor Index
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last updated on 2024-08-25 19:09 CEST by the dblp team
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