Zobrazeno 1 - 10
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pro vyhledávání: '"Rafferty, Amy"'
The rapidly advancing field of Explainable Artificial Intelligence (XAI) aims to tackle the issue of trust regarding the use of complex black-box deep learning models in real-world applications. Existing post-hoc XAI techniques have recently been sho
Externí odkaz:
http://arxiv.org/abs/2403.19444
The Stereotype Content model (SCM) states that we tend to perceive minority groups as cold, incompetent or both. In this paper we adapt existing work to demonstrate that the Stereotype Content model holds for contextualised word embeddings, then use
Externí odkaz:
http://arxiv.org/abs/2210.14552
Publikováno v:
Ungless, E, Rafferty, A, Nag, H & Ross, B 2023, A robust bias mitigation procedure based on the Stereotype Content model . in D Bamman, D Hovy, D Jurgens, K Keith, B O'Connor & S Volkova (eds), Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science . pp. 207-217, The 5th Workshop on Natural Language Processing and Computational Social Science, Abu Dhabi, United Arab Emirates, 7/12/22 . < https://arxiv.org/abs/2210.14552v1 >
The Stereotype Content model (SCM) states that we tend to perceive minority groups as cold, incompetent or both. In this paper we adapt existing work to demonstrate that the Stereotype Content model holds for contextualised word embeddings, then use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3094::ab9232ddce53a433be7b0de28aa52937
https://hdl.handle.net/20.500.11820/4972924a-c6b1-4566-a350-0c66f69d6940
https://hdl.handle.net/20.500.11820/4972924a-c6b1-4566-a350-0c66f69d6940
Publikováno v:
Rafferty, A, Nenutil, R & Rajan, A 2022, Explainable Artificial Intelligence for Breast Tumour Classification: Helpful or Harmful . in M Reyes, P H Abreu & J Cardoso (eds), Interpretability of Machine Intelligence in Medical Image Computing: 5th International Workshop, iMIMIC 2022, Held in Conjunction with MICCAI 2022, Singapore, Singapore, September 22, 2022, Proceedings . Lecture Notes in Computer Science, vol. 13611, pp. 104-123, Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2022, Singapore, 22/09/22 . https://doi.org/10.1007/978-3-031-17976-1_10
Explainable Artificial Intelligence (XAI) is the field of AI dedicated to promoting trust in machine learning models by helping us to understand how they make their decisions. For example, image explanations show us which pixels or segments were deem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3094::bd076e31e830460ae8d5a28999e96f33
https://hdl.handle.net/20.500.11820/3b1f9902-1bb8-4bf2-a185-7b053f7eb81d
https://hdl.handle.net/20.500.11820/3b1f9902-1bb8-4bf2-a185-7b053f7eb81d
Autor:
Rafferty, Amy Beth
Publikováno v:
Dissertations, Theses, and Masters Projects.
Externí odkaz:
https://scholarworks.wm.edu/etd/1539625821
https://scholarworks.wm.edu/cgi/viewcontent.cgi?article=5354&context=etd
https://scholarworks.wm.edu/cgi/viewcontent.cgi?article=5354&context=etd
Autor:
Goomany, Anand1 anandg@doctors.org.uk, Rafferty, Amy1 amy.rafferty@bthft.nhs.uk, Smith, Ian1 iansmith@bthft.nhs.uk
Publikováno v:
Case Reports in Surgery. 5/7/2015, Vol. 2015, p1-4. 4p.
Autor:
Rafferty, Amy1 (AUTHOR) amyrafferty@doctors.org.uk, Martin, Jane1 (AUTHOR), Strachan, David1 (AUTHOR), Raine, Chris1 (AUTHOR)
Publikováno v:
Cochlear Implants International: An Interdisciplinary Journal. Mar2013, Vol. 14 Issue 2, p61-66. 6p.
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