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of 584
pro vyhledávání: '"Duchesnay, A."'
Contrastive Analysis is a sub-field of Representation Learning that aims at separating common factors of variation between two datasets, a background (i.e., healthy subjects) and a target (i.e., diseased subjects), from the salient factors of variati
Externí odkaz:
http://arxiv.org/abs/2402.11928
Contrastive Analysis VAE (CA-VAEs) is a family of Variational auto-encoders (VAEs) that aims at separating the common factors of variation between a background dataset (BG) (i.e., healthy subjects) and a target dataset (TG) (i.e., patients) from the
Externí odkaz:
http://arxiv.org/abs/2307.06206
Building accurate Deep Learning (DL) models for brain age prediction is a very relevant topic in neuroimaging, as it could help better understand neurodegenerative disorders and find new biomarkers. To estimate accurate and generalizable models, larg
Externí odkaz:
http://arxiv.org/abs/2211.08326
Autor:
Pierre-Yves Postic, Yann Leprince, Soraya Brosset, Laure Drutel, Emeline Peyric, Ines Ben Abdallah, Dhaif Bekha, Sara Neumane, Edouard Duchesnay, Mickael Dinomais, Mathilde Chevignard, Lucie Hertz-Pannier
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
IntroductionEarly focal brain injuries lead to long-term disabilities with frequent cognitive impairments, suggesting global dysfunction beyond the lesion. While plasticity of the immature brain promotes better learning, outcome variability across in
Externí odkaz:
https://doaj.org/article/2cf7262ba82b49e98582ceaf93d807c0
Autor:
Benoit Dufumier, Pietro Gori, Sara Petiton, Robin Louiset, Jean-François Mangin, Antoine Grigis, Edouard Duchesnay
Publikováno v:
NeuroImage, Vol 296, Iss , Pp 120665- (2024)
The perspective of personalized medicine for brain disorders requires efficient learning models for anatomical neuroimaging-based prediction of clinical conditions. There is now a consensus on the benefit of deep learning (DL) in addressing many medi
Externí odkaz:
https://doaj.org/article/6185c233d77248ac97b35bdc87d5448c
Data augmentation is a crucial component in unsupervised contrastive learning (CL). It determines how positive samples are defined and, ultimately, the quality of the learned representation. In this work, we open the door to new perspectives for CL b
Externí odkaz:
http://arxiv.org/abs/2206.01646
Contrastive Learning has shown impressive results on natural and medical images, without requiring annotated data. However, a particularity of medical images is the availability of meta-data (such as age or sex) that can be exploited for learning rep
Externí odkaz:
http://arxiv.org/abs/2111.05643
Autor:
Dufumier, Benoit, Gori, Pietro, Petiton, Sara, Louiset, Robin, Mangin, Jean-François, Grigis, Antoine, Duchesnay, Edouard
Publikováno v:
In NeuroImage 1 August 2024 296
Autor:
Louiset, Robin, Gori, Pietro, Dufumier, Benoit, Houenou, Josselin, Grigis, Antoine, Duchesnay, Edouard
Publikováno v:
ECML/PKDD 2021
Subtype Discovery consists in finding interpretable and consistent sub-parts of a dataset, which are also relevant to a certain supervised task. From a mathematical point of view, this can be defined as a clustering task driven by supervised learning
Externí odkaz:
http://arxiv.org/abs/2107.01988
Autor:
Fountoulakis, Konstantinos N., Vrublevska, Jelena, Abraham, Seri, Adorjan, Kristina, Ahmed, Helal Uddin, Alarcón, Renato D., Arai, Kiyomi, Auwal, Sani Salihu, Berk, Michael, Bjedov, Sarah, Bobes, Julio, Bobes-Bascaran, Teresa, Bourgin-Duchesnay, Julie, Bredicean, Cristina Ana, Bukelskis, Laurynas, Burkadze, Akaki, Abud, Indira Indiana Cabrera, Castilla-Puentes, Ruby, Cetkovich, Marcelo, Colon-Rivera, Hector, Corral, Ricardo, Cortez-Vergara, Carla, Crepin, Piirika, De Berardis, Domenico, Delgado, Sergio Zamora, De Lucena, David, De Sousa, Avinash, Di Stefano, Ramona, Dodd, Seetal, Elek, Livia Priyanka, Elissa, Anna, Erdelyi-Hamza, Berta, Erzin, Gamze, Etchevers, Martin J., Falkai, Peter, Farcas, Adriana, Fedotov, Ilya, Filatova, Viktoriia, Fountoulakis, Nikolaos K., Frankova, Iryna, Franza, Francesco, Frias, Pedro, Galako, Tatiana, Garay, Cristian J., Garcia-Álvarez, Leticia, García-Portilla, Maria Paz, Gonda, Xenia, Gondek, Tomasz M., González, Daniela Morera, Gould, Hilary, Grandinetti, Paolo, Grau, Arturo, Groudeva, Violeta, Hagin, Michal, Harada, Takayuki, Hasan, Tasdik M., Hashim, Nurul Azreen, Hilbig, Jan, Hossain, Sahadat, Iakimova, Rossitza, Ibrahim, Mona, Iftene, Felicia, Ignatenko, Yulia, Irarrazaval, Matias, Ismail, Zaliha, Ismayilova, Jamila, Jacobs, Asaf, Jakovljević, Miro, Jakšić, Nenad, Javed, Afzal, Kafali, Helin Yilmaz, Karia, Sagar, Kazakova, Olga, Khalifa, Doaa, Khaustova, Olena, Koh, Steve, Kosenko, Korneliia, Koupidis, Sotirios A., Lalljee, Alisha, Liewig, Justine, Majid, Abdul, Malashonkova, Evgeniia, Malik, Khamelia, Malik, Najma Iqbal, Mammadzada, Gulay, Mandalia, Bilvesh, Marazziti, Donatella, Marčinko, Darko, Martinez, Stephanie, Matiekus, Eimantas, Mejia, Gabriela, Memon, Roha Saeed, Martínez, Xarah Elenne Meza, Mickevičiūtė, Dalia, Milev, Roumen, Mohammed, Muftau, Molina-López, Alejandro, Morozov, Petr, Muhammad, Nuru Suleiman, Mustač, Filip, Naor, Mika S., Nassieb, Amira, Navickas, Alvydas, Okasha, Tarek, Pandova, Milena, Panfil, Anca-Livia, Panteleeva, Liliya, Papava, Ion, Patsali, Mikaella E., Pavlichenko, Alexey, Pejuskovic, Bojana, Da Costa, Mariana Pinto, Popkov, Mikhail, Popovic, Dina, Raduan, Nor Jannah Nasution, Ramírez, Francisca Vargas, Rancans, Elmars, Razali, Salmi, Rebok, Federico, Rewekant, Anna, Flores, Elena Ninoska Reyes, Rivera-Encinas, María Teresa, Saiz, Pilar, de Carmona, Manuel Sánchez, Martínez, David Saucedo, Saw, Jo Anne, Saygili, Görkem, Schneidereit, Patricia, Shah, Bhumika, Shirasaka, Tomohiro, Silagadze, Ketevan, Sitanggang, Satti, Skugarevsky, Oleg, Spikina, Anna, Mahalingappa, Sridevi Sira, Stoyanova, Maria, Szczegielniak, Anna, Tamasan, Simona Claudia, Tavormina, Giuseppe, Tavormina, Maurilio Giuseppe Maria, Theodorakis, Pavlos N., Tohen, Mauricio, Tsapakis, Eva Maria, Tukhvatullina, Dina, Ullah, Irfan, Vaidya, Ratnaraj, Vega-Dienstmaier, Johann M., Vukovic, Olivera, Vysotska, Olga, Widiasih, Natalia, Yashikhina, Anna, Smirnova, Daria
Publikováno v:
In Journal of Affective Disorders 1 May 2024 352:536-551