| Variability in the analysis of a single neuroimaging dataset by many teams R Botvinik-Nezer, F Holzmeister, CF Camerer, A Dreber, J Huber, ... Nature 582 (7810), 84-88, 2020 | 137 | 2020 |
| Benchmarking functional connectome-based predictive models for resting-state fMRI K Dadi, M Rahim, A Abraham, D Chyzhyk, M Milham, B Thirion, ... NeuroImage 192, 115-134, 2019 | 78 | 2019 |
| Variability in the analysis of a single neuroimaging dataset by many teams. BioRxiv, 843193 R Botvinik-Nezer, F Holzmeister, CF Camerer, A Dreber, J Huber, ... | 5 | 2019 |
| Fine-grain atlases of functional modes for fMRI analysis K Dadi, G Varoquaux, A Machlouzarides-Shalit, KJ Gorgolewski, ... NeuroImage 221, 117126, 2020 | 4 | 2020 |
| Loading and plotting of cortical surface representations in Nilearn J Huntenburg, A Abraham, J Loula, F Liem, K Dadi, G Varoquaux Research Ideas and Outcomes 3, e12342, 2017 | 4 | 2017 |
| Comparing functional connectivity based predictive models across datasets K Dadi, A Abraham, M Rahim, B Thirion, G Varoquaux 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI), 1-4, 2016 | 4 | 2016 |
| Variability in the analysis of a single neuroimaging dataset by many teams (Preprint) R Botvinik-Nezer, F Holzmeister, CF Camerer, A Dreber, J Huber, ... | 1 | 2020 |
| Machine learning on population imaging for mental health KR Dadi Université Paris-Saclay, 2020 | | 2020 |
| Beyond brain age: Empirically-derived proxy measures of mental health K Dadi, G Varoquaux, J Houenou, D Bzdok, B Thirion, D Engemann | | 2020 |
| Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging F Liem, K Dadi, DA Engemann, A Gramfort, P Bellec, RC Craddock, ... bioRxiv, 2020 | | 2020 |
| What’s in a functional brain parcellation? G Varoquaux, K Dadi, A Mensch | | 2019 |
| Circadian Rhythms in the Brain-A first step KR Dadi | | 2013 |
| HBP Data Descriptor K Dadi, G Varoquaux, A Machlouzarides-Shalita, KJ Gorgolewskic, ... | | |
