| Cabozantinib versus everolimus, nivolumab, axitinib, sorafenib and best supportive care: a network meta-analysis of progression-free survival and overall survival in second … B Amzal, S Fu, J Meng, J Lister, H Karcher PloS one 12 (9), e0184423, 2017 | 62 | 2017 |
| Estimating discrete Markov models from various incomplete data schemes A Pasanisi, S Fu, N Bousquet Computational Statistics & Data Analysis 56 (9), 2609-2625, 2012 | 28 | 2012 |
| Bayesian inference for inverse problems occurring in uncertainty analysis S Fu, G Celeux, N Bousquet, M Couplet International Journal for Uncertainty Quantification 5 (1), 2015 | 18 | 2015 |
| Cabozantinib versus standard-of-care comparators in the treatment of advanced/metastatic renal cell carcinoma in treatment-naive patients: a systematic review and network meta … E Schmidt, J Lister, M Neumann, W Wiecek, S Fu, AL Vataire, J Sostar, ... Targeted Oncology 13, 205-216, 2018 | 15 | 2018 |
| An adaptive kriging method for solving nonlinear inverse statistical problems S Fu, M Couplet, N Bousquet Environmetrics 28 (4), e2439, 2017 | 12 | 2017 |
| Hierarchical Bayesian LASSO for a negative binomial regression S Fu Journal of Statistical Computation and Simulation 86 (11), 2182-2203, 2016 | 12 | 2016 |
| Second-line cabozantinib versus nivolumab in advanced renal cell carcinoma: Systematic review and indirect treatment comparison C Porta, C Szczylik, R Casciano, S Fu, B Amzal, J Lister, H Karcher, ... Critical Reviews in Oncology/Hematology 139, 143-148, 2019 | 11 | 2019 |
| Effect of stomatal control on Populus simonii Carr stand transpiration in farmland shelterbelt, China’s semi-arid region S Fu, Y Xiao, Y Luo, L Sun, D Wu Agroforestry Systems 94, 719-731, 2020 | 10 | 2020 |
| A hierarchical Bayesian approach to negative binomial regression S Fu Methods and Applications of Analysis 22 (4), 409-428, 2015 | 10 | 2015 |
| The “RCT augmentation”: a novel simulation method to add patient heterogeneity into phase III trials H Karcher, S Fu, J Meng, MZ Ankarfeldt, O Efthimiou, M Belger, JM Haro, ... BMC Medical research methodology 18, 1-14, 2018 | 4 | 2018 |
| Multivariate analysis of Co, Fe and Ni leaching from tailings following simulated temperature change S Fu, JM Lu, FQ Yuan IOP Conference Series: Earth and Environmental Science 191 (1), 012125, 2018 | 4 | 2018 |
| Inverse problems occurring in uncertainty analysis S Fu Université Paris Sud-Paris XI, 2012 | 2 | 2012 |
| PRM152-A GENERIC BAYESIAN DES MODEL FOR MULTI-STATE DISEASE PROGRESSION B Amzal, S Fu, Z Angehrn Value in Health 21, S382, 2018 | 1 | 2018 |
| Optimal design of pre-authorization trials for effectiveness evaluation in severe asthma H Karcher, J Meng, S Fu, E Loefroth, H Cao, E Peress Value in Health 19 (7), A360-A361, 2016 | 1 | 2016 |
| A practical guide to adding patient heterogeneity into phase III trials: results from IMI GetReal WP2 H Karcher, S Fu, C Nordon, O Efthimiou, S Schneeweiss, L Abenhaim Value in Health 18 (7), A727, 2015 | 1 | 2015 |
| Estimation de modèles markoviens discrets dans un cadre industriel fiabiliste à données manquantes A Pasanisi, S Fu, N Bousquet 42èmes Journées de Statistique, 2010 | 1 | 2010 |
| Understanding the Spatial Spreads and Spectral Breaks of Gradual SEP Events: Applying iPATH Simulations to SEP Observations. J Hu, C Cohen, G Zank, G Li, R Mewaldt, S Fu 42nd COSPAR Scientific Assembly 42, D2. 1-30-18, 2018 | | 2018 |
| Forecasting and nowcasting of solar energetic particle environment using the iPATH model S Fu, Y Jiang, G Li, J Hu AGU Fall Meeting Abstracts 2017, SH41B-2769, 2017 | | 2017 |
| OPTIMAL DESIGN OF PRE-AUTHORIZATION TRIALS FOR EFFECTIVENESS EVALUATION IN SCHIZOPHRENIA H Karcher, S Fu, ZM Ankarfeldt, JM Haro, C Nordon VALUE IN HEALTH 20 (5), A314-A314, 2017 | | 2017 |
| A Bayesian solution to characterizing uncertainty in inverse problems S Fu, N Bousquet Journées des doctorants, GdR MASCOT-NUM, 2011 | | 2011 |