Zobrazeno 1 - 10
of 4 633
pro vyhledávání: '"David, Jean"'
Autor:
AskariHemmat, MohammadHossein, Jeddi, Ahmadreza, Hemmat, Reyhane Askari, Lazarevich, Ivan, Hoffman, Alexander, Sah, Sudhakar, Saboori, Ehsan, Savaria, Yvon, David, Jean-Pierre
Quantization lowers memory usage, computational requirements, and latency by utilizing fewer bits to represent model weights and activations. In this work, we investigate the generalization properties of quantized neural networks, a characteristic th
Externí odkaz:
http://arxiv.org/abs/2404.11769
Autor:
Hirtz, Jason, David, Jean-Christophe, Cugnon, Joseph, Leya, Ingo, Rodríguez-Sánchez, José Luís, Schnabel, Georg
The accuracy and precision of high-energy spallation models are key issues for the design and development of new applications and experiments. We present a method to estimate model parameters and associated uncertainties by leveraging the Bayesian ve
Externí odkaz:
http://arxiv.org/abs/2312.01993
Autor:
Danièle Henky
Publikováno v:
Revue des sciences religieuses. :418-420
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26a1e370634a9a2052d7fe0b8df94e8f
https://doi.org/10.4000/rsr.13080
https://doi.org/10.4000/rsr.13080
Autor:
Ershova, Anna, Niewczas, Kajetan, Bolognesi, Sara, Letourneau, Alain, David, Jean-Christophe, Rodríguez-Sánchez, José Luís, Sobczyk, Jan, Blanchet, Adrien, Avanzini, Margherita Buizza, Chakrani, Jaafar, Cugnon, Joseph, Dolan, Stephen, Giganti, Claudio, Hassani, Samira, Hirtz, Jason, Joshi, Shivam, Juszczak, Cezary, Munteanu, Laura, Sgalaberna, Davide, Yevarouskaya, Uladzislava
Present and next generation of long-baseline accelerator experiments are bringing the measurement of neutrino oscillations into the precision era with ever-increasing statistics. One of the most challenging aspects of achieving such measurements is d
Externí odkaz:
http://arxiv.org/abs/2309.05410
Autor:
Henky, Danièle
Dans l’œuvre prolifique de Jean Giono se rencontrent des préoccupations philosophiques et des formes esthétiques multiples. D. Perrin a souhaité, dans un volume particulièrement riche et bien structuré, s’intéresser aux rapports que l’au
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::e879546062dbc52af87d3c8157932ac3
http://journals.openedition.org/rsr/13080
http://journals.openedition.org/rsr/13080
Autor:
Segeroth, Martin1 (AUTHOR), Winkel, David Jean1 (AUTHOR), Kaufmann, Beat A.2 (AUTHOR), Strebel, Ivo2 (AUTHOR), Yang, Shan3 (AUTHOR), Cyriac, Joshy3 (AUTHOR), Wasserthal, Jakob3 (AUTHOR), Bach, Michael1 (AUTHOR), Lopez-Ayala, Pedro2 (AUTHOR), Sauter, Alexander1 (AUTHOR), Mueller, Christian2 (AUTHOR), Bremerich, Jens1 (AUTHOR), Zellweger, Michael2 (AUTHOR), Haaf, Philip2 (AUTHOR) philip.haaf@usb.ch, Gallegos-Funes, Francisco (AUTHOR) fgallegosf@ipn.mx
Publikováno v:
International Journal of Biomedical Imaging. 10/28/2024, Vol. 2024, p1-10. 10p.
Autor:
Dupuis, Théo, Fournier, Yoan, AskariHemmat, MohammadHossein, Zarif, Nizar El, Leduc-Primeau, François, David, Jean Pierre, Savaria, Yvon
Convolutional Neural Networks (CNNs) are used in a wide range of applications, with full-precision CNNs achieving high accuracy at the expense of portability. Recent progress in quantization techniques has demonstrated that sub-byte Quantized Neural
Externí odkaz:
http://arxiv.org/abs/2306.09905