| Environment‐Wide Association Study (EnWAS) of Prenatal and Perinatal Factors Associated With Autistic Traits: A Population‐Based Study M Amiri, S Lamballais, E Geenjaar, LME Blanken, H El Marroun, ... Autism Research 13 (9), 1582-1600, 2020 | 21 | 2020 |
| Algorithm-agnostic explainability for unsupervised clustering CA Ellis, MSE Sendi, E Geenjaar, SM Plis, RL Miller, VD Calhoun arXiv preprint arXiv:2105.08053, 2021 | 18 | 2021 |
| Self-supervised multimodal domino: in search of biomarkers for alzheimer’s disease A Fedorov, T Sylvain, E Geenjaar, M Luck, L Wu, TP DeRamus, A Kirilin, ... 2021 IEEE 9th International Conference on Healthcare Informatics (ICHI), 23-30, 2021 | 12* | 2021 |
| Neurodevelopmental trajectories in children with internalizing, externalizing and emotion dysregulation symptoms E Blok, EPT Geenjaar, EAW Geenjaar, VD Calhoun, T White Frontiers in Psychiatry 13, 846201, 2022 | 7 | 2022 |
| Fusing multimodal neuroimaging data with a variational autoencoder E Geenjaar, N Lewis, Z Fu, R Venkatdas, S Plis, V Calhoun 2021 43rd Annual International Conference of the IEEE Engineering in …, 2021 | 7 | 2021 |
| Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data A Fedorov, E Geenjaar, L Wu, TP DeRamus, VD Calhoun, SM Plis arXiv preprint arXiv:2103.15914, 2021 | 5 | 2021 |
| Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures E Geenjaar, T White, V Calhoun 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2021 | 4 | 2021 |
| Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes A Fedorov, E Geenjaar, L Wu, T Sylvain, TP DeRamus, M Luck, M Misiura, ... arXiv preprint arXiv:2209.02876, 2022 | 2 | 2022 |
| Spatio-temporally separable non-linear latent factor learning: an application to somatomotor cortex fMRI data E Geenjaar, A Kashyap, N Lewis, R Miller, V Calhoun arXiv preprint arXiv:2205.13640, 2022 | 2 | 2022 |
| Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links A Fedorov, E Geenjaar, L Wu, T Sylvain, TP DeRamus, M Luck, M Misiura, ... NeuroImage 285, 120485, 2024 | 1 | 2024 |
| Chromatic fusion: Generative multimodal neuroimaging data fusion provides multi‐informed insights into schizophrenia EPT Geenjaar, NL Lewis, A Fedorov, L Wu, JM Ford, A Preda, SM Plis, ... Human Brain Mapping 44 (17), 5828-5845, 2023 | 1 | 2023 |
| Learning low-dimensional dynamics from whole-brain data improves task capture E Geenjaar, D Kim, R Ohib, M Duda, A Kashyap, S Plis, V Calhoun arXiv preprint arXiv:2305.14369, 2023 | 1 | 2023 |
| Uncovering the latent dynamics of whole-brain fMRI tasks with a sequential variational autoencoder E Geenjaar, D Kim, R Ohib, M Duda, A Kashyap, SM Plis, V Calhoun Deep Generative Models for Health Workshop NeurIPS 2023, 2023 | | 2023 |
| Using an ODE model to separate Rest and Task signals in fMRI A Kashyap, E Geenjaar, P Bey, K Dhindsa, K Glomb, S Plis, S Keilholz, ... bioRxiv, 2023.10. 23.563564, 2023 | | 2023 |
| CommsVAE: Learning the brain's macroscale communication dynamics using coupled sequential VAEs E Geenjaar, N Lewis, A Kashyap, R Miller, V Calhoun NeurIPs - Medical Imaging meets NeurIPs, 2022 | | 2022 |
| Mind the gap: functional network connectivity interpolation between schizophrenia patients and controls using a variational autoencoder X Li, E Geenjaar, Z Fu, S Plis, V Calhoun 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | | 2022 |
| Voxelwise rs-fMRI representation learning: A non-linear variational approach E Geenjaar | | 2021 |
Vince D. CalhounDirector-Translational Research in Neuroimaging and Data Science (TReNDS;GSU/GAtech/Emory)Geverifieerd e-mailadres voor gsu.edu
