Zobrazeno 1 - 10
of 86 686
pro vyhledávání: '"AT Gillespie"'
As generative AI technologies find more and more real-world applications, the importance of testing their performance and safety seems paramount. ``Red-teaming'' has quickly become the primary approach to test AI models--prioritized by AI companies,
Externí odkaz:
http://arxiv.org/abs/2412.09751
Autor:
Beck, T., Gade, A., Brown, B. A., Utsuno, Y., Weisshaar, D., Bazin, D., Brown, K. W., Charity, R. J., Farris, P. J., Gillespie, S. A., Hill, A. M., Li, J., Longfellow, B., Reviol, W., Rhodes, D.
High-resolution in-beam $\gamma$-ray spectroscopy was used to study excited states of the neutron-deficient nucleus $^{32}$Ar populated in fast-beam induced four- and six-nucleon removal reactions from $^{36,38}$Ca. One new $\gamma$-ray transition an
Externí odkaz:
http://arxiv.org/abs/2412.05404
Autor:
Beck, T., Gade, A., Brown, B. A., Weisshaar, D., Bazin, D., Brown, K. W., Charity, R. J., Farris, P. J., Gillespie, S. A., Hill, A. M., Li, J., Longfellow, B., Reviol, W., Rhodes, D.
Publikováno v:
Phys. Rev. C 110, 014305 (2024)
In-beam $\gamma$-ray spectroscopy was used to study excited states of the neutron-deficient nucleus $^{37}$K populated in fast-beam inelastic-scattering and proton-removal reactions at high-momentum loss. New $\gamma$-ray transitions and $\gamma\gamm
Externí odkaz:
http://arxiv.org/abs/2411.15563
Autor:
Fonollosa, Laia Garrobé, Gillespie, Douglas, Stankovic, Lina, Stankovic, Vladimir, Rendell, Luke
Passive acoustic monitoring (PAM) data is often weakly labelled, audited at the scale of detection presence or absence on timescales of minutes to hours. Moreover, this data exhibits great variability from one deployment to the next, due to differenc
Externí odkaz:
http://arxiv.org/abs/2410.17006
Autor:
Sierra, Elena, Gillespie, Lauren E., Soltani, Salim, Exposito-Alonso, Moises, Kattenborn, Teja
Climate change is negatively impacting the world's biodiversity. To build automated systems to monitor these negative biodiversity impacts, large-scale, volunteer-collected datasets like iNaturalist are built from community-identified, natural imager
Externí odkaz:
http://arxiv.org/abs/2410.19816
Equipping graph neural networks with a convolution operation defined in terms of a cellular sheaf offers advantages for learning expressive representations of heterophilic graph data. The most flexible approach to constructing the sheaf is to learn i
Externí odkaz:
http://arxiv.org/abs/2410.09590
Autor:
Caune, Laura, Skoric, Luka, Blunt, Nick S., Ruban, Archibald, McDaniel, Jimmy, Valery, Joseph A., Patterson, Andrew D., Gramolin, Alexander V., Majaniemi, Joonas, Barnes, Kenton M., Bialas, Tomasz, Buğdaycı, Okan, Crawford, Ophelia, Gehér, György P., Krovi, Hari, Matekole, Elisha, Topal, Canberk, Poletto, Stefano, Bryant, Michael, Snyder, Kalan, Gillespie, Neil I., Jones, Glenn, Johar, Kauser, Campbell, Earl T., Hill, Alexander D.
Quantum error correction (QEC) will be essential to achieve the accuracy needed for quantum computers to realise their full potential. The field has seen promising progress with demonstrations of early QEC and real-time decoded experiments. As quantu
Externí odkaz:
http://arxiv.org/abs/2410.05202
Autor:
Huynh, Andy V., Gillespie, Lauren E., Lopez-Saucedo, Jael, Tang, Claire, Sikand, Rohan, Expósito-Alonso, Moisés
Multimodal image-text contrastive learning has shown that joint representations can be learned across modalities. Here, we show how leveraging multiple views of image data with contrastive learning can improve downstream fine-grained classification p
Externí odkaz:
http://arxiv.org/abs/2409.19439
Autor:
Kim, Inwook, Bray, Connor, Marino, Andrew, Stone-Whitehead, Caitlyn, Lamm, Amii, Abells, Ryan, Amaro, Pedro, Andoche, Adrien, Cantor, Robin, Diercks, David, Fretwell, Spencer, Gillespie, Abigail, Guerra, Mauro, Hall, Ad, Harris, Cameron N., Harris, Jackson T., Hinkle, Calvin, Hayen, Leendert M., Hervieux, Paul-Antoine, Kim, Geon-Bo, Leach, Kyle G., Lennarz, Annika, Lordi, Vincenzo, Machado, Jorge, McKeen, David, Mougeot, Xavier, Ponce, Francisco, Ruiz, Chris, Samanta, Amit, Santos, José Paulo, Smolsky, Joseph, Taylor, John, Templet, Joseph, Upadhyayula, Sriteja, Wagner, Louis, Warburton, William K., Waters, Benjamin, Friedrich, Stephan
The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for evidence of heavy neutrino mass eigenstates in the nuclear electron capture decay of $^7$Be by precisely measuring the recoil energy of the $^7$Li daug
Externí odkaz:
http://arxiv.org/abs/2409.19085
Autor:
Puri, Sandeep, Lin, Cuikun, Gillespie, Andrew, Jones, Ian, Carty, Christopher, Kelley, Mitchell, Weed, Ryan, Duncan, Robert V.
In this article, we present our recent experiments on fission fragment rocket propulsion, and on an innovative new design for an alpha particle detection system that has been inspired by these rocketry results. Our test platform, which operates withi
Externí odkaz:
http://arxiv.org/abs/2409.15206