| 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 | 497 | 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 | 357 | 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 | 260 | 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 | 169 | 2020 |
| 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 | 146 | 2010 |
| 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 | 141 | 2021 |
| Topological and dynamical complexity of random neural networks G Wainrib, J Touboul Physical review letters 110 (11), 118101, 2013 | 128 | 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 | 105 | 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 | 85 | 2019 |
| A local echo state property through the largest Lyapunov exponent G Wainrib, MN Galtier Neural Networks 76, 39-45, 2016 | 60 | 2016 |
| Limit theorems for infinite-dimensional piecewise deterministic Markov processes. Applications to stochastic excitable membrane models M Riedler, M Thieullen, G Wainrib | 50 | 2012 |
| 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 | 45 | 2019 |
| 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 | 41 | 2020 |
| 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 | 39 | 2012 |
| Synchronization in random balanced networks LCG Del Molino, K Pakdaman, J Touboul, G Wainrib Physical Review E 88 (4), 042824, 2013 | 36 | 2013 |
| Intrinsic variability of latency to first-spike W Gilles, T Michèle, P Khashayar Biological cybernetics 103 (1), 43-56, 2010 | 36 | 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 | 32 | 2018 |
| The asymptotic performance of linear echo state neural networks R Couillet, G Wainrib, H Sevi, HT Ali The Journal of Machine Learning Research 17 (1), 6171-6205, 2016 | 31 | 2016 |
| 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 | 28 | 2021 |
| Asymptotic expansion and central limit theorem for multiscale piecewise-deterministic Markov processes K Pakdaman, M Thieullen, G Wainrib Stochastic Processes and their Applications 122 (6), 2292-2318, 2012 | 26 | 2012 |
Mikhail ZaslavskiyBestätigte E-Mail-Adresse bei ensmp.fr
