Zobrazeno 1 - 10
of 902
pro vyhledávání: '"Gravelle P"'
Autor:
Ding, Mucong, Xu, Yuancheng, Rabbani, Tahseen, Liu, Xiaoyu, Gravelle, Brian, Ranadive, Teresa, Tuan, Tai-Ching, Huang, Furong
Dataset condensation can be used to reduce the computational cost of training multiple models on a large dataset by condensing the training dataset into a small synthetic set. State-of-the-art approaches rely on matching the model gradients between t
Externí odkaz:
http://arxiv.org/abs/2405.17535
Autor:
Laukemann, Jan, Helal, Ahmed E., Anderson, S. Isaac Geronimo, Checconi, Fabio, Soh, Yongseok, Tithi, Jesmin Jahan, Ranadive, Teresa, Gravelle, Brian J, Petrini, Fabrizio, Choi, Jee
High-dimensional sparse data emerge in many critical application domains such as cybersecurity, healthcare, anomaly detection, and trend analysis. To quickly extract meaningful insights from massive volumes of these multi-dimensional data, scientists
Externí odkaz:
http://arxiv.org/abs/2403.06348
Autor:
Berkman, Sophie, Cerati, Giuseppe, Elmer, Peter, Gartung, Patrick, Giannini, Leonardo, Gravelle, Brian, Hall, Allison R., Kortelainen, Matti, Krutelyov, Vyacheslav, Lantz, Steve R., Masciovecchio, Mario, McDermott, Kevin, Norris, Boyana, Reid, Michael, Riley, Daniel S., Tadel, Matevž, Vourliotis, Emmanouil, Wang, Bei, Wittich, Peter, Yagil, Avraham
One of the most challenging computational problems in the Run 3 of the Large Hadron Collider (LHC) and more so in the High-Luminosity LHC (HL-LHC) is expected to be finding and fitting charged-particle tracks during event reconstruction. The methods
Externí odkaz:
http://arxiv.org/abs/2304.05853
Autor:
Gravelle P. C.
Publikováno v:
Oil & Gas Science and Technology, Vol 32, Iss 2, Pp 283-292 (2006)
Externí odkaz:
https://doaj.org/article/418d3fa8c23a470da4aa5235ffd205ce
Autor:
France Gravelle, Martin Maltais
Publikováno v:
Médiations & Médiatisations, Iss 17 (2024)
Les domaines de l'éducation (Gravelle, Frigon et Monette, 2020) et de l'enseignement supérieur (Maltais, Ness, Jungblut et Rexe, 2023) sont en mutation mondiale, confrontés à des défis croissants. À l'ère du numérique, les établissements d
Externí odkaz:
https://doaj.org/article/3c462c5c70094f0abfba9f3245aac240
Autor:
Julie Monette, France Gravelle
Publikováno v:
Médiations & Médiatisations, Iss 17 (2024)
Cette note de lecture résume les principales conclusions d’un mémoire de maîtrise portant sur la relation pédagogique en formation à distance (FAD). Les résultats de cette recherche démontrent qu’en contexte de FAD, bien que plus de la moi
Externí odkaz:
https://doaj.org/article/17707a95215c499787f9c2d2101c0520
Autor:
Berkman, Sophie, Cerati, Giuseppe, Knoepfel, Kyle, Mengel, Marc, Hall, Allison Reinsvold, Wang, Michael, Gravelle, Brian, Norris, Boyana
Neutrinos are particles that interact rarely, so identifying them requires large detectors which produce lots of data. Processing this data with the computing power available is becoming even more difficult as the detectors increase in size to reach
Externí odkaz:
http://arxiv.org/abs/2107.00812
Autor:
Cerati, Giuseppe, Elmer, Peter, Gravelle, Brian, Kortelainen, Matti, Krutelyov, Vyacheslav, Lantz, Steven, Masciovecchio, Mario, McDermott, Kevin, Norris, Boyana, Hall, Allison Reinsvold, Reid, Micheal, Riley, Daniel, Tadel, Matevž, Wittich, Peter, Wang, Bei, Würthwein, Frank, Yagil, Avraham
We present results from parallelizing the unpacking and clustering steps of the raw data from the silicon strip modules for reconstruction of charged particle tracks. Throughput is further improved by concurrently processing multiple events using nes
Externí odkaz:
http://arxiv.org/abs/2101.11489
Autor:
Misael Anaya-Montes, Hugh Gravelle
Publikováno v:
PLoS ONE, Vol 19, Iss 8 (2024)
Externí odkaz:
https://doaj.org/article/bedf58359ada4b5eab2bb16601964f60
Autor:
Lantz, Steven, McDermott, Kevin, Reid, Michael, Riley, Daniel, Wittich, Peter, Berkman, Sophie, Cerati, Giuseppe, Kortelainen, Matti, Hall, Allison Reinsvold, Elmer, Peter, Wang, Bei, Giannini, Leonardo, Krutelyov, Vyacheslav, Masciovecchio, Mario, Tadel, Matevž, Würthwein, Frank, Yagil, Avraham, Gravelle, Brian, Norris, Boyana
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is determining the trajectory of charged particles during event reconstruction. Algorithms used at the LHC today rely on Kalman filte
Externí odkaz:
http://arxiv.org/abs/2006.00071