| 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 | 871 | 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 | 291 | 2019 |
| Fine-grain atlases of functional modes for fMRI analysis K Dadi, G Varoquaux, A Machlouzarides-Shalit, KJ Gorgolewski, ... NeuroImage 221, 117126, 2020 | 86 | 2020 |
| Brainhack: Developing a culture of open, inclusive, community-driven neuroscience R Gau, S Noble, K Heuer, KL Bottenhorn, IP Bilgin, YF Yang, ... Neuron 109 (11), 1769-1775, 2021 | 34 | 2021 |
| Population modeling with machine learning can enhance measures of mental health K Dadi, G Varoquaux, J Houenou, D Bzdok, B Thirion, D Engemann GigaScience 10 (10), giab071, 2021 | 31 | 2021 |
| 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 | 15 | 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 | 11 | 2016 |
| Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging BH Vieira, F Liem, K Dadi, DA Engemann, A Gramfort, P Bellec, ... Neurobiology of aging 118, 55-65, 2022 | 10 | 2022 |
| Deep learning approach for classification and interpretation of autism spectrum disorder PKC Prasad, Y Khare, K Dadi, PK Vinod, BR Surampudi 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 5 | 2022 |
| Beyond brain age: Empirically-derived proxy measures of mental health K Dadi, G Varoquaux, J Houenou, D Bzdok, B Thirion, D Engemann | 5 | 2020 |
| mulEEG: a multi-view representation learning on EEG signals V Kumar, L Reddy, S Kumar Sharma, K Dadi, C Yarra, RS Bapi, ... International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 4 | 2022 |
| Variability in the analysis of a single neuroimaging dataset by many teams (Preprint) R Botvinik-Nezer, F Holzmeister, CF Camerer, A Dreber, J Huber, ... | 2 | 2020 |
| HyperGALE: ASD Classification via Hypergraph Gated Attention with Learnable Hyperedges M Arora, CS Jain, LB Baru, K Dadi, BR Surampudi arXiv preprint arXiv:2403.14484, 2024 | | 2024 |
| BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision P Deb, LB Baru, K Dadi arXiv preprint arXiv:2310.07060, 2023 | | 2023 |
| Dynamic functional connectivity analysis in individuals with Autism Spectrum Disorder PKC Prasad, K Dadi, BR Surampudi 2023 International Joint Conference on Neural Networks (IJCNN), 1-7, 2023 | | 2023 |
| Big Data in Cognitive Neuroscience: Opportunities and Challenges K Dadi, BR Surampudi International Conference on Big Data Analytics, 16-30, 2022 | | 2022 |
| Machine learning on population imaging for mental health K Dadi Université Paris-Saclay, 2020 | | 2020 |
| What’s in a functional brain parcellation? G Varoquaux, K Dadi, A Mensch Real Neurons {\&} Hidden Units: Future directions at the intersection of …, 2019 | | 2019 |
| Circadian Rhythms in the Brain-A first step KR Dadi | | 2013 |
| SUBJECT E Jordan, A Keshavan, ML Mandelli, R Henry, A Klein, K Vohland, ... Unresolved Safety Issues: Pressurized Thermal Shock: Oversight Hearing …, 1984 | | 1984 |
