| Sloan digital sky survey IV: Mapping the Milky Way, nearby galaxies, and the distant universe MR Blanton, MA Bershady, B Abolfathi, FD Albareti, CA Prieto, A Almeida, ... The Astronomical Journal 154 (1), 28, 2017 | 1603 | 2017 |
| The fourteenth data release of the sloan digital sky survey: First spectroscopic data from the extended baryon oscillation spectroscopic survey and from the second phase of the … B Abolfathi, DS Aguado, G Aguilar, CA Prieto, A Almeida, TT Ananna, ... The Astrophysical Journal Supplement Series 235 (2), 42, 2018 | 1106 | 2018 |
| The 13th data release of the Sloan Digital Sky Survey: First spectroscopic data from the SDSS-IV survey mapping nearby galaxies at Apache Point Observatory FD Albareti, CA Prieto, A Almeida, F Anders, S Anderson, BH Andrews, ... The Astrophysical Journal Supplement Series 233 (2), 25, 2017 | 597 | 2017 |
| Autoencoders WHL Pinaya, S Vieira, R Garcia-Dias, A Mechelli Machine learning, 193-208, 2020 | 149 | 2020 |
| The fifteenth data release of the Sloan Digital Sky Surveys: first release of MaNGA-derived quantities, data visualization tools, and stellar library DS Aguado, R Ahumada, A Almeida, SF Anderson, BH Andrews, ... The Astrophysical Journal Supplement Series 240 (2), 23, 2019 | 111 | 2019 |
| Convolutional neural networks WHL Pinaya, S Vieira, R Garcia-Dias, A Mechelli Machine learning, 173-191, 2020 | 89 | 2020 |
| Machine learning for brain age prediction: Introduction to methods and clinical applications L Baecker, R Garcia-Dias, S Vieira, C Scarpazza, A Mechelli EBioMedicine 72, 2021 | 85 | 2021 |
| Machine learning: methods and applications to brain disorders A Mechelli, S Vieira Academic Press, 2019 | 78 | 2019 |
| Chemical Abundances of Main-sequence, Turnoff, Subgiant, and Red Giant Stars from APOGEE Spectra. II. Atomic Diffusion in M67 Stars D Souto, CA Prieto, K Cunha, M Pinsonneault, VV Smith, R Garcia-Dias, ... The Astrophysical Journal 874 (1), 97, 2019 | 75 | 2019 |
| Brain age prediction: A comparison between machine learning models using region‐and voxel‐based morphometric data L Baecker, J Dafflon, PF Da Costa, R Garcia‐Dias, S Vieira, C Scarpazza, ... Human brain mapping 42 (8), 2332-2346, 2021 | 73 | 2021 |
| The Pristine survey – VI. The first three years of medium-resolution follow-up spectroscopy of Pristine EMP star candidates DS Aguado, K Youakim, JI González Hernández, C Allende Prieto, ... Monthly Notices of the Royal Astronomical Society 490 (2), 2241-2253, 2019 | 72 | 2019 |
| The Pristine survey–X. A large population of low-metallicity stars permeates the Galactic disc F Sestito, NF Martin, E Starkenburg, A Arentsen, RA Ibata, N Longeard, ... Monthly Notices of the Royal Astronomical Society: Letters 497 (1), L7-L12, 2020 | 70 | 2020 |
| Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners R Garcia-Dias, C Scarpazza, L Baecker, S Vieira, WHL Pinaya, A Corvin, ... Neuroimage 220, 117127, 2020 | 57 | 2020 |
| OCCASO–II. Physical parameters and Fe abundances of red clump stars in 18 open clusters L Casamiquela, R Carrera, S Blanco-Cuaresma, C Jordi, ... Monthly Notices of the Royal Astronomical Society 470 (4), 4363-4381, 2017 | 49 | 2017 |
| Clustering analysis R Garcia-Dias, S Vieira, WHL Pinaya, A Mechelli machine learning, 227-247, 2020 | 47 | 2020 |
| Using normative modelling to detect disease progression in mild cognitive impairment and Alzheimer’s disease in a cross-sectional multi-cohort study WHL Pinaya, C Scarpazza, R Garcia-Dias, S Vieira, L Baecker, ... Scientific reports 11 (1), 15746, 2021 | 45 | 2021 |
| Translating research findings into clinical practice: a systematic and critical review of neuroimaging-based clinical tools for brain disorders C Scarpazza, M Ha, L Baecker, R Garcia-Dias, WHL Pinaya, S Vieira, ... Translational Psychiatry 10 (1), 107, 2020 | 36 | 2020 |
| Machine learning in APOGEE-Unsupervised spectral classification with K-means R Garcia-Dias, CA Prieto, JS Almeida, I Ordovás-Pascual Astronomy & Astrophysics 612, A98, 2018 | 25 | 2018 |
| Bridge over troubled gas: clusters and associations under the SMC and LMC tidal stresses E Bica, B Santiago, C Bonatto, R Garcia-Dias, L Kerber, B Dias, B Barbuy, ... Monthly Notices of the Royal Astronomical Society 453 (3), 3190-3202, 2015 | 23 | 2015 |
| Deep neural networks S Vieira, WHL Pinaya, R Garcia-Dias, A Mechelli Machine learning, 157-172, 2020 | 17 | 2020 |
Sandra VieiraInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonVerified email at kcl.ac.uk
