Zobrazeno 1 - 10
of 14 208
pro vyhledávání: '"Fahy, A"'
Learning to optimize is an approach that leverages training data to accelerate the solution of optimization problems. Many approaches use unrolling to parametrize the update step and learn optimal parameters. Although L2O has shown empirical advantag
Externí odkaz:
http://arxiv.org/abs/2406.00260
Autor:
Juyal, Dinkar, Padigela, Harshith, Shah, Chintan, Shenker, Daniel, Harguindeguy, Natalia, Liu, Yi, Martin, Blake, Zhang, Yibo, Nercessian, Michael, Markey, Miles, Finberg, Isaac, Luu, Kelsey, Borders, Daniel, Javed, Syed Ashar, Krause, Emma, Biju, Raymond, Sood, Aashish, Ma, Allen, Nyman, Jackson, Shamshoian, John, Chhor, Guillaume, Sanghavi, Darpan, Thibault, Marc, Yu, Limin, Najdawi, Fedaa, Hipp, Jennifer A., Fahy, Darren, Glass, Benjamin, Walk, Eric, Abel, John, Pokkalla, Harsha, Beck, Andrew H., Grullon, Sean
Pathology is the study of microscopic inspection of tissue, and a pathology diagnosis is often the medical gold standard to diagnose disease. Pathology images provide a unique challenge for computer-vision-based analysis: a single pathology Whole Sli
Externí odkaz:
http://arxiv.org/abs/2405.07905
Monolayers of growing bacteria, confined within channel geometries, exhibit self-organization into a highly aligned laminar state along the axis of the channel. Although this phenomenon has been observed in experiments and simulations under various b
Externí odkaz:
http://arxiv.org/abs/2401.17222
Autor:
Fahy, Conor, Yang, Shengxiang
Recognising and reacting to change in non-stationary data-streams is a challenging task. The majority of research in this area assumes that the true class label of incoming points are available, either at each time step or intermittently with some la
Externí odkaz:
http://arxiv.org/abs/2312.14948
A scanning helium microscope typically utilises a thermal energy helium atom beam, with an energy and wavelength (<100 meV, ~0.05 nm) particularly sensitive to surface structure. An angular detector stage for a scanning helium microscope is presented
Externí odkaz:
http://arxiv.org/abs/2310.06247
Autor:
Huang, Yijing, Querales-Flores, José D., Teitelbaum, Samuel W., Cao, Jiang, Henighan, Thomas, Liu, Hanzhe, Jiang, Mason, De la Peña, Gilberto, Krapivin, Viktor, Haber, Johann, Sato, Takahiro, Chollet, Matthieu, Zhu, Diling, Katayama, Tetsuo, Power, Robert, Allen, Meabh, Rotundu, Costel R., Bailey, Trevor P., Uher, Ctirad, Trigo, Mariano, Kirchmann, Patrick S., Murray, Éamonn D., Shen, Zhi-Xun, Savic, Ivana, Fahy, Stephen, Sobota, Jonathan A., Reis, David A.
Quantifying electron-phonon interactions for the surface states of topological materials can provide key insights into surface-state transport, topological superconductivity, and potentially how to manipulate the surface state using a structural degr
Externí odkaz:
http://arxiv.org/abs/2307.12132
As the search for exoplanets continues, more are being discovered orbiting Red Giant stars. We use current data from the NASA Exoplanet Archive to investigate planet distribution around Red Giant stars and their presence in the host's habitable zone.
Externí odkaz:
http://arxiv.org/abs/2307.04975
Publikováno v:
Leadership & Organization Development Journal, 2024, Vol. 45, Issue 5, pp. 877-898.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/LODJ-04-2022-0199
Autor:
Jiang, Jonathan H., Berea, Anamaria, Bowden, Heather, Das, Prithwis, Fahy, Kristen A., Ginsberg, Joseph, Jew, Robert, Jiang, Xiaoming, Kershenbaum, Arik, Kipping, David, Lau, Graham, Lewis, Karen, Lendo, C. Isabel Nunez, Rosen, Philip E., Searra, Nick, Taylor, Stuart F., Traphagan, John
Publikováno v:
Earth and Space Science, Vol. 10, Issue 12, 2023
In this first part of our series, we delve into the foundational aspects of the "Message in a Bottle" (henceforth referred to as MIAB). This study stands as a continuation of the legacy set by the Voyager Golden Records launched aboard Voyager 1 and
Externí odkaz:
http://arxiv.org/abs/2306.01765
Autor:
Gullapally, Sai Chowdary, Zhang, Yibo, Mittal, Nitin Kumar, Kartik, Deeksha, Srinivasan, Sandhya, Rose, Kevin, Shenker, Daniel, Juyal, Dinkar, Padigela, Harshith, Biju, Raymond, Minden, Victor, Maheshwari, Chirag, Thibault, Marc, Goldstein, Zvi, Novak, Luke, Chandra, Nidhi, Lee, Justin, Prakash, Aaditya, Shah, Chintan, Abel, John, Fahy, Darren, Taylor-Weiner, Amaro, Sampat, Anand
Machine learning algorithms have the potential to improve patient outcomes in digital pathology. However, generalization of these tools is currently limited by sensitivity to variations in tissue preparation, staining procedures and scanning equipmen
Externí odkaz:
http://arxiv.org/abs/2305.02401