Zobrazeno 1 - 10
of 5 634
pro vyhledávání: '"Eyre, P."'
Autor:
Eyre, Benjamin, Madras, David
Continually evaluating large generative models provides a unique challenge. Often, human annotations are necessary to evaluate high-level properties of these models (e.g. in text or images). However, collecting human annotations of samples can be res
Externí odkaz:
http://arxiv.org/abs/2411.12665
Autor:
Prodan, Ante, Occhipinti, Jo-An, Ahlip, Rehez, Ujdur, Goran, Eyre, Harris A., Goosen, Kyle, Penza, Luke, Heffernan, Mark
This paper explores the nuanced landscape of generative AI (genAI), particularly focusing on neural network-based models like Large Language Models (LLMs). While genAI garners both optimistic enthusiasm and sceptical criticism, this work seeks to pro
Externí odkaz:
http://arxiv.org/abs/2410.16629
Autor:
Rogers, Mitchell, Knowles, Kobe, Gendron, Gaël, Heidari, Shahrokh, Valdez, David Arturo Soriano, Azhar, Mihailo, O'Leary, Padriac, Eyre, Simon, Witbrock, Michael, Delmas, Patrice
Deep learning approaches for animal re-identification have had a major impact on conservation, significantly reducing the time required for many downstream tasks, such as well-being monitoring. We propose a method called Recurrence over Video Frames
Externí odkaz:
http://arxiv.org/abs/2406.13002
Autor:
Occhipinti, Jo-An, Hynes, William, Prodan, Ante, Eyre, Harris A., Green, Roy, Burrow, Sharan, Tanner, Marcel, Buchanan, John, Ujdur, Goran, Destrebecq, Frederic, Song, Christine, Carnevale, Steven, Hickie, Ian B., Heffernan, Mark
Work is fundamental to societal prosperity and mental health, providing financial security, identity, purpose, and social integration. The emergence of generative artificial intelligence (AI) has catalysed debate on job displacement. Some argue that
Externí odkaz:
http://arxiv.org/abs/2407.01545
Autor:
Occhipinti, Jo-An, Prodan, Ante, Hynes, William, Green, Roy, Burrow, Sharan, Eyre, Harris A, Skinner, Adam, Ujdur, Goran, Buchanan, John, Hickie, Ian B, Heffernan, Mark, Song, Christine, Tanner, Marcel
Generative Artificial Intelligence (AI) stands as a transformative force that presents a paradox; it offers unprecedented opportunities for productivity growth while potentially posing significant threats to economic stability and societal wellbeing.
Externí odkaz:
http://arxiv.org/abs/2403.17405
Autor:
Anderson, Evan J. D., Eyre, Christopher K., Dailey, Isabel M., Rozpędek, Filip, Bash, Boulat A.
We explore covert communication of qubits over the lossy thermal-noise bosonic channel, which is a quantum-mechanical model of many practical channels, including optical. Covert communication ensures that an adversary is unable to detect the presence
Externí odkaz:
http://arxiv.org/abs/2401.06764
Designing deep neural network classifiers that perform robustly on distributions differing from the available training data is an active area of machine learning research. However, out-of-distribution generalization for regression-the analogous probl
Externí odkaz:
http://arxiv.org/abs/2312.17463
Autor:
Gendron, Gaël, Chen, Yang, Rogers, Mitchell, Liu, Yiping, Azhar, Mihailo, Heidari, Shahrokh, Valdez, David Arturo Soriano, Knowles, Kobe, O'Leary, Padriac, Eyre, Simon, Witbrock, Michael, Dobbie, Gillian, Liu, Jiamou, Delmas, Patrice
Better understanding the natural world is a crucial task with a wide range of applications. In environments with close proximity between humans and animals, such as zoos, it is essential to better understand the causes behind animal behaviour and wha
Externí odkaz:
http://arxiv.org/abs/2312.14333
Autor:
Lipsitch, Marc, Bassett, Mary T., Brownstein, John S., Elliott, Paul, Eyre, David, Grabowski, M. Kate, Hay, James A., Johansson, Michael, Kissler, Stephen M., Larremore, Daniel B., Layden, Jennifer, Lessler, Justin, Lynfield, Ruth, MacCannell, Duncan, Madoff, Lawrence C., Metcalf, C. Jessica E., Meyers, Lauren A., Ofori, Sylvia K., Quinn, Celia, Bento, Ana I. Ramos, Reich, Nick, Riley, Steven, Rosenfeld, Roni, Samore, Matthew H., Sampath, Rangarajan, Slayton, Rachel B., Swerdlow, David L., Truelove, Shaun, Varma, Jay K., Grad, Yonatan H.
The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss r
Externí odkaz:
http://arxiv.org/abs/2311.13724
Autor:
Jia Wei, Jiandong Zhou, Zizheng Zhang, Kevin Yuan, Qingze Gu, Augustine Luk, Andrew J. Brent, David A. Clifton, A. Sarah Walker, David W. Eyre
Publikováno v:
Communications Medicine, Vol 4, Iss 1, Pp 1-14 (2024)
Abstract Background Accurately predicting hospital discharge events could help improve patient flow and the efficiency of healthcare delivery. However, using machine learning and diverse electronic health record (EHR) data for this task remains incom
Externí odkaz:
https://doaj.org/article/f06c8a54ca284a09804811017394d711
