1 code implementation • 17 Dec 2023 • Al-Harith Farhad, Ioannis Sorokos, Mohammed Naveed Akram, Koorosh Aslansefat, Daniel Schneider
The zeitgeist of the digital era has been dominated by an expanding integration of Artificial Intelligence~(AI) in a plethora of applications across various domains.
1 code implementation • 13 Nov 2023 • Koorosh Aslansefat, Mojgan Hashemian, Martin Walker, Mohammed Naveed Akram, Ioannis Sorokos, Yiannis Papadopoulos
Machine learning is currently undergoing an explosion in capability, popularity, and sophistication.
no code implementations • 23 Nov 2022 • Sohag Kabir, Koorosh Aslansefat, Prosanta Gope, Felician Campean, Yiannis Papadopoulos
Effective operation and maintenance that ensures the maximum availability of the energy generation process using offshore facilities and minimal production cost are two key factors to improve the competitiveness of this energy source over other traditional sources of energy.
1 code implementation • 19 Jul 2022 • Connor Walker, Callum Rothon, Koorosh Aslansefat, Yiannis Papadopoulos, Nina Dethlefs
With an increasing emphasis on driving down the costs of Operations and Maintenance (O&M) in the Offshore Wind (OSW) sector, comes the requirement to explore new methodology and applications of Deep Learning (DL) to the domain.
1 code implementation • 11 Jul 2022 • Al-Harith Farhad, Ioannis Sorokos, Andreas Schmidt, Mohammed Naveed Akram, Koorosh Aslansefat, Daniel Schneider
Limitations in setting SafeML up properly include the lack of a systematic approach for determining, for a given application, how many operational samples are needed to yield reliable distance information as well as to determine an appropriate distance threshold.
2 code implementations • 17 Jun 2022 • Mohammed Naveed Akram, Akshatha Ambekar, Ioannis Sorokos, Koorosh Aslansefat, Daniel Schneider
This work focuses on the use of SafeML for time series data, and on reliability and robustness estimation of ML-forecasting methods using statistical distance measures.
1 code implementation • Computer 2021 • Koorosh Aslansefat, Sohag Kabir, Amr Abdullatif, Vinod Vasudevan Nair, Yiannis Papadopoulos
The application of artificial intelligence (AI) and data-driven decision-making systems in autonomous vehicles is growing rapidly.
2 code implementations • 27 May 2020 • Koorosh Aslansefat, Ioannis Sorokos, Declan Whiting, Ramin Tavakoli Kolagari, Yiannis Papadopoulos
Ensuring safety and explainability of machine learning (ML) is a topic of increasing relevance as data-driven applications venture into safety-critical application domains, traditionally committed to high safety standards that are not satisfied with an exclusive testing approach of otherwise inaccessible black-box systems.
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