Gilles Wainrib
Gilles Wainrib
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Zitiert von
Zitiert von
A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series
S Chambon, MN Galtier, PJ Arnal, G Wainrib, A Gramfort
IEEE Transactions on Neural Systems and Rehabilitation Engineering 26 (4 …, 2018
Deep learning-based classification of mesothelioma improves prediction of patient outcome
P Courtiol, C Maussion, M Moarii, E Pronier, S Pilcer, M Sefta, ...
Nature medicine 25 (10), 1519-1525, 2019
A deep learning model to predict RNA-Seq expression of tumours from whole slide images
B Schmauch, A Romagnoni, E Pronier, C Saillard, P Maillé, J Calderaro, ...
Nature communications 11 (1), 3877, 2020
Predicting survival after hepatocellular carcinoma resection using deep learning on histological slides
C Saillard, B Schmauch, O Laifa, M Moarii, S Toldo, M Zaslavskiy, ...
Hepatology 72 (6), 2000-2013, 2020
Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients
N Lassau, S Ammari, E Chouzenoux, H Gortais, P Herent, M Devilder, ...
Nature communications 12 (1), 1-11, 2021
Fluid limit theorems for stochastic hybrid systems with application to neuron models
K Pakdaman, M Thieullen, G Wainrib
Advances in Applied Probability 42 (3), 761-794, 2010
Topological and dynamical complexity of random neural networks
G Wainrib, J Touboul
Physical review letters 110 (11), 118101, 2013
Classification and disease localization in histopathology using only global labels: A weakly-supervised approach
P Courtiol, EW Tramel, M Sanselme, G Wainrib
arXiv preprint arXiv:1802.02212, 2018
Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
A Romagnoni, S Jégou, K Van Steen, G Wainrib, JP Hugot
Scientific reports 9 (1), 10351, 2019
A local echo state property through the largest Lyapunov exponent
G Wainrib, MN Galtier
Neural Networks 76, 39-45, 2016
Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer
J Ogier du Terrail, A Leopold, C Joly, C Béguier, M Andreux, C Maussion, ...
Nature medicine 29 (1), 135-146, 2023
Limit theorems for infinite-dimensional piecewise deterministic Markov processes. Applications to stochastic excitable membrane models
M Riedler, M Thieullen, G Wainrib
Comprehensive molecular and pathologic evaluation of transitional mesothelioma assisted by deep learning approach: a multi-institutional study of the International Mesothelioma …
FG Salle, N Le Stang, F Tirode, P Courtiol, AG Nicholson, MS Tsao, ...
Journal of thoracic oncology 15 (6), 1037-1053, 2020
Colonic MicroRNA profiles, identified by a deep learning algorithm, that predict responses to therapy of patients with acute severe ulcerative colitis
I Morilla, M Uzzan, D Laharie, D Cazals-Hatem, Q Denost, F Daniel, ...
Clinical Gastroenterology and Hepatology 17 (5), 905-913, 2019
Reduction of stochastic conductance-based neuron models with time-scales separation
G Wainrib, M Thieullen, K Pakdaman
Journal of computational neuroscience 32 (2), 327-346, 2012
Synchronization in random balanced networks
LCG Del Molino, K Pakdaman, J Touboul, G Wainrib
Physical Review E 88 (4), 042824, 2013
Intrinsic variability of latency to first-spike
W Gilles, T Michèle, P Khashayar
Biological cybernetics 103 (1), 43-56, 2010
Scaling up echo-state networks with multiple light scattering
J Dong, S Gigan, F Krzakala, G Wainrib
2018 IEEE Statistical Signal Processing Workshop (SSP), 448-452, 2018
A deep learning method for predicting knee osteoarthritis radiographic progression from MRI
JB Schiratti, R Dubois, P Herent, D Cahané, J Dachary, T Clozel, ...
Arthritis Research & Therapy 23, 1-10, 2021
The asymptotic performance of linear echo state neural networks
R Couillet, G Wainrib, H Sevi, HT Ali
Journal of Machine Learning Research 17 (178), 1-35, 2016
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