Zobrazeno 1 - 10
of 63 973
pro vyhledávání: '"Karen, M"'
Autor:
Srivastava, Divya, Feigh, Karen M.
Recommender systems, while a powerful decision making tool, are often operationalized as black box models, such that their AI algorithms are not accessible or interpretable by human operators. This in turn can cause confusion and frustration for the
Externí odkaz:
http://arxiv.org/abs/2409.10717
Microelectronic magnetic sensors are essential in diverse applications, including automotive, industrial, and consumer electronics. Hall-effect devices hold the largest share of the magnetic sensor market, and they are particularly valued for their r
Externí odkaz:
http://arxiv.org/abs/2409.04333
Autor:
Petrenko, Svetlana, Page, Karen M.
The rapid and complex patterning of biosilica in diatom frustules is of great interest in nanotechnology, although it remains incompletely understood. Specific organic molecules, including long-chain polyamines, silaffins, and silacidins are essentia
Externí odkaz:
http://arxiv.org/abs/2405.08496
Autor:
Green, Kaylie S., Gallagher, Sarah C., Leighly, Karen M., Choi, Hyunseop, Grupe, Dirk, Terndrup, Donald M., Richards, Gordon T., Komossa, S.
Publikováno v:
2023, ApJ, 953, 186
Broad Absorption Line Quasars (BALQs) are actively accreting supermassive black holes that have strong outflows characterized by broad absorption lines in their rest-UV spectra. Variability in these absorption lines occurs over months to years depend
Externí odkaz:
http://arxiv.org/abs/2405.06027
Autor:
Bischetti, Manuela, Choi, Hyunseop, Fiore, Fabrizio, Feruglio, Chiara, Carniani, Stefano, D'Odorico, Valentina, Bañados, Eduardo, Chen, Huanqing, Decarli, Roberto, Gallerani, Simona, Hlavacek-Larrondo, Julie, Lai, Samuel, Leighly, Karen M., Mazzucchelli, Chiara, Perreault-Levasseur, Laurence, Tripodi, Roberta, Walter, Fabian, Wang, Feige, Yang, Jinyi, Zanchettin, Maria Vittoria, Zhu, Yongda
Although the mass growth of supermassive black holes during the Epoch of Reionisation is expected to play a role in shaping the concurrent growth of their host-galaxies, observational evidence of feedback at z$\gtrsim$6 is still sparse. We perform th
Externí odkaz:
http://arxiv.org/abs/2404.12443
This paper presents an incremental replanning algorithm, dubbed LTL-D*, for temporal-logic-based task planning in a dynamically changing environment. Unexpected changes in the environment may lead to failures in satisfying a task specification in the
Externí odkaz:
http://arxiv.org/abs/2404.01219
Autor:
Kolb, Jack, Feigh, Karen M.
We investigate the real-time estimation of human situation awareness using observations from a robot teammate with limited visibility. In human factors and human-autonomy teaming, it is recognized that individuals navigate their environments using an
Externí odkaz:
http://arxiv.org/abs/2403.11955
Autor:
Leighly, Karen M., Choi, Hyunseop, Eracleous, Michael, Terndrup, Donald M., Gallagher, Sarah C., Richards, Gordon T.
We present the optical-near infrared spectral energy distributions (SED) and near infrared variability properties of 30 low-redshift iron low-ionization Broad Absorption Line quasars (FeLoBALQs) and matched samples of LoBALQs and unabsorbed quasars.
Externí odkaz:
http://arxiv.org/abs/2402.07855
In private computation, a user wishes to retrieve a function evaluation of messages stored on a set of databases without revealing the function's identity to the databases. Obead \emph{et al.} introduced a capacity outer bound for private nonlinear c
Externí odkaz:
http://arxiv.org/abs/2401.06125
Autor:
Capraro, Valerio, Lentsch, Austin, Acemoglu, Daron, Akgun, Selin, Akhmedova, Aisel, Bilancini, Ennio, Bonnefon, Jean-François, Brañas-Garza, Pablo, Butera, Luigi, Douglas, Karen M., Everett, Jim A. C., Gigerenzer, Gerd, Greenhow, Christine, Hashimoto, Daniel A., Holt-Lunstad, Julianne, Jetten, Jolanda, Johnson, Simon, Longoni, Chiara, Lunn, Pete, Natale, Simone, Rahwan, Iyad, Selwyn, Neil, Singh, Vivek, Suri, Siddharth, Sutcliffe, Jennifer, Tomlinson, Joe, van der Linden, Sander, Van Lange, Paul A. M., Wall, Friederike, Van Bavel, Jay J., Viale, Riccardo
Generative artificial intelligence has the potential to both exacerbate and ameliorate existing socioeconomic inequalities. In this article, we provide a state-of-the-art interdisciplinary overview of the potential impacts of generative AI on (mis)in
Externí odkaz:
http://arxiv.org/abs/2401.05377