Zobrazeno 1 - 10
of 763
pro vyhledávání: '"A. Morisot"'
Autor:
Dang, John, Singh, Shivalika, D'souza, Daniel, Ahmadian, Arash, Salamanca, Alejandro, Smith, Madeline, Peppin, Aidan, Hong, Sungjin, Govindassamy, Manoj, Zhao, Terrence, Kublik, Sandra, Amer, Meor, Aryabumi, Viraat, Campos, Jon Ander, Tan, Yi-Chern, Kocmi, Tom, Strub, Florian, Grinsztajn, Nathan, Flet-Berliac, Yannis, Locatelli, Acyr, Lin, Hangyu, Talupuru, Dwarak, Venkitesh, Bharat, Cairuz, David, Yang, Bowen, Chung, Tim, Ko, Wei-Yin, Shi, Sylvie Shang, Shukayev, Amir, Bae, Sammie, Piktus, Aleksandra, Castagné, Roman, Cruz-Salinas, Felipe, Kim, Eddie, Crawhall-Stein, Lucas, Morisot, Adrien, Roy, Sudip, Blunsom, Phil, Zhang, Ivan, Gomez, Aidan, Frosst, Nick, Fadaee, Marzieh, Ermis, Beyza, Üstün, Ahmet, Hooker, Sara
We introduce the Aya Expanse model family, a new generation of 8B and 32B parameter multilingual language models, aiming to address the critical challenge of developing highly performant multilingual models that match or surpass the capabilities of m
Externí odkaz:
http://arxiv.org/abs/2412.04261
Autor:
Aryabumi, Viraat, Su, Yixuan, Ma, Raymond, Morisot, Adrien, Zhang, Ivan, Locatelli, Acyr, Fadaee, Marzieh, Üstün, Ahmet, Hooker, Sara
Including code in the pre-training data mixture, even for models not specifically designed for code, has become a common practice in LLMs pre-training. While there has been anecdotal consensus among practitioners that code data plays a vital role in
Externí odkaz:
http://arxiv.org/abs/2408.10914
Autor:
Mindermann, Sören, Brauner, Jan, Razzak, Muhammed, Sharma, Mrinank, Kirsch, Andreas, Xu, Winnie, Höltgen, Benedikt, Gomez, Aidan N., Morisot, Adrien, Farquhar, Sebastian, Gal, Yarin
Training on web-scale data can take months. But most computation and time is wasted on redundant and noisy points that are already learnt or not learnable. To accelerate training, we introduce Reducible Holdout Loss Selection (RHO-LOSS), a simple but
Externí odkaz:
http://arxiv.org/abs/2206.07137
Autor:
Moreno, Santiago, Burns, Fiona, Campo, Rafael Eduardo, Garges, Harmony, Mussini, Cristina, Pantazis, Nikos, Kamel, Moustafa, Porter, Kholoud, Sabin, Caroline, Tariq, Shema, Touloumi, Giota, Vannappagari, Vani, Anne, Alain Volny, Young, Lital, Gill, John, Carlander, Christina, Grabar, Sophie, Jarrín, Inma, Meyer, Laurence, van der Valk, Marc, Wittkop, Linda, Aisam, Agnes, Barger, Diana, Davidovich, Udi, Dos Santos, Marie, Eriksson, Lars, Fitzgerald, Eli, Karakosta, Argyro, Krentz, Hartmut, Nicholls, Emily Jay, Policek, Nicoletta, Ruiz-Burga, Elisa, Sandford, Chris, Spire, Bruno, Suárez-García, Inés, Abgrall, Sophie, Andriantsoanirina, Valerie, Avettand-Fenoel, Veronique, Bourgeois, Christine, Chaix, Marie-Laure, Cheret, Antoine, Fischer, Hugues, Goujard, Cecile, Lascoux-Combe, Caroline, Le Palec, Annie, Petrov-Sanchez, Ventzlislava, Saez-Cirion, Asier, Seng, Remonie, Stefic, Karl, Tine, Josephine, Piet, E, Gagneux-Brunon, A, Jacomet, C, Piroth, L, Benezit, F, Goussef, M, Tattevin, P, Bani Sadr, B, Lamaury, I, Bazus, H, Robineau, O, Calin, R, Katlama, J, Denis, B, Ghosn, J, Joly, V, Khuong, M A, Caby, F C, Rouveix Nordon, E, de Truchis, P, Abgrall, S, Chéret, A, Duvivier, C, Becker, A, Miailhes, P, Abel, S, Unal, G, Makinson, A, Martin-Blondel, G, Morisot, A, Bregigeon, S, Enel, P, Allavena, C, Rabier, V, Vallet, L, Marchand, L, Saïdi, T, Costagliola, D, Grabar, S, Andriantsoanirina, V, Fischer, H, Marchand T Saïdi, L, Tattevin, Pierre, de Truchis, Pierre, Fischer, Hughes, Dalmau, David, Navarro, M Luisa, González, M Isabel, Garcia, Federico, Poveda, Eva, Iribarren, Jose Antonio, Gutiérrez, Félix, Rubio, Rafael, Vidal, Francesc, Berenguer, Juan, Muñoz-Fernández, M Ángeles, Adamis, G, Chini, M, Chrysos, G, Marangos, M, Katsarou, O, Kofteridis, D, Metallidis, S, Panagopoulos, P, Papadopoulos, A, Paparizos, V, Psychogiou, M, Sambatakou, H, Sipsas, N V, Touloumi, G, Fox, Julie, Terry, Louise, Waters, Anele, Uriel, Alison, Ustianowski, Andrew, Hackney, Pamela, Fahd, Niaz, Fidler, Sarah, Ayap, Wilbert, Molina, Marcelino, Waters, Laura, Nur, Fowsiya, Fernandez, Thomas, Nugent, Diarmuid, Pinedo, Javier, Reeves, Iain, Fong, Tracy, Nicholls, Jane, Cunningham, Laura, Pangan, Jaydee, Mackintosh, Claire, Sharp, Louise, Sabin, Caroline A, Van der Valk, Marc, Jarrin, Inma, van Sighem, Ard, Volny Anne, Alain, Costagliola, Dominique
Publikováno v:
In The Lancet HIV October 2024 11(10):e660-e669
Autor:
Angela Puma, Nicolae Grecu, Raluca Ș. Badea, Adeline Morisot, Roxana Zugravu, Mihai B. Ioncea, Michele Cavalli, Oana Lăcătuș, Andra Ezaru, Chorfa Hacina, Luisa Villa, Charles Raffaelli, Nicolas Azulay, Sabrina Sacconi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract To date, little is known about the usefulness of ultra-high frequency ultrasound (UHF-US, 50–70 MHz) in clinical practice for the diagnosis of dysimmune neuropathies. We present a prospective study aimed at comparing UHF-US alterations of
Externí odkaz:
https://doaj.org/article/14d23869b6c5464db9538beec8614e2a
Autor:
Ngo, Helen, Raterink, Cooper, Araújo, João G. M., Zhang, Ivan, Chen, Carol, Morisot, Adrien, Frosst, Nicholas
Language models trained on large-scale unfiltered datasets curated from the open web acquire systemic biases, prejudices, and harmful views from their training data. We present a methodology for programmatically identifying and removing harmful text
Externí odkaz:
http://arxiv.org/abs/2108.07790
Autor:
Mindermann, Sören, Razzak, Muhammed, Xu, Winnie, Kirsch, Andreas, Sharma, Mrinank, Morisot, Adrien, Gomez, Aidan N., Farquhar, Sebastian, Brauner, Jan, Gal, Yarin
Publikováno v:
ICML 2021 Workshop on Subset Selection in Machine Learning
We introduce Goldilocks Selection, a technique for faster model training which selects a sequence of training points that are "just right". We propose an information-theoretic acquisition function -- the reducible validation loss -- and compute it wi
Externí odkaz:
http://arxiv.org/abs/2107.02565
Autor:
Morisot, Adrien
As the performance and popularity of deep neural networks has increased, so too has their computational cost. There are many effective techniques for reducing a network's computational footprint (quantisation, pruning, knowledge distillation), but th
Externí odkaz:
http://arxiv.org/abs/2007.13512
Autor:
Mirzai, N., Polet, K., Louchart de la Chapelle, S., Hesse, S., Morisot, A., Pesce, A., Galy, E.
Publikováno v:
In NPG Neurologie - Psychiatrie - Gériatrie December 2023 23(138):410-422
Autor:
Anne Calleja, Michael Loschi, Laurent Bailly, Adeline Morisot, Alice Marceau, Lionel Mannone, Guillaume Robert, Patrick Auberger, Claude Preudhomme, Sophie Raynaud, Fabien Subtil, Pierre Sujobert, Thomas Cluzeau
Publikováno v:
Cancer Medicine, Vol 12, Iss 5, Pp 5656-5660 (2023)
Abstract Personalized medicine is a challenge for patients with acute myeloid leukemia (AML). The identification of several genetic mutations in several AML trials led to the creation of a personalized prognostic scoring algorithm known as the Knowle
Externí odkaz:
https://doaj.org/article/d992efe825594a8d9a57c31cda98a4ed