| Tracing the cosmic web NI Libeskind, R Van De Weygaert, M Cautun, B Falck, E Tempel, T Abel, ... Monthly Notices of the Royal Astronomical Society 473 (1), 1195-1217, 2018 | 326 | 2018 |
| The SPTPoL extended cluster survey LE Bleem, S Bocquet, B Stalder, MD Gladders, PAR Ade, SW Allen, ... The Astrophysical Journal Supplement Series 247 (1), 25, 2020 | 186 | 2020 |
| Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning K Fukami, R Maulik, N Ramachandra, K Fukagata, K Taira Nature Machine Intelligence 3 (11), 945-951, 2021 | 131 | 2021 |
| Probabilistic neural networks for fluid flow surrogate modeling and data recovery R Maulik, K Fukami, N Ramachandra, K Fukagata, K Taira Physical Review Fluids 5 (10), 104401, 2020 | 108 | 2020 |
| Beyond the hubble sequence–exploring galaxy morphology with unsupervised machine learning TY Cheng, M Huertas-Company, CJ Conselice, A Aragon-Salamanca, ... Monthly Notices of the Royal Astronomical Society 503 (3), 4446-4465, 2021 | 47 | 2021 |
| Matter power spectrum emulator for modified gravity cosmologies N Ramachandra, G Valogiannis, M Ishak, K Heitmann, ... Physical Review D 103 (12), 123525, 2021 | 41 | 2021 |
| Multi-stream portrait of the cosmic web NS Ramachandra, SF Shandarin Monthly Notices of the Royal Astronomical Society 452 (2), 1643-1653, 2015 | 41 | 2015 |
| Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation R Maulik, T Botsas, N Ramachandra, LR Mason, I Pan Physica D: Nonlinear Phenomena 416, 132797, 2021 | 35 | 2021 |
| Anomaly detection in Hyper Suprime-Cam galaxy images with generative adversarial networks K Storey-Fisher, M Huertas-Company, N Ramachandra, F Lanusse, ... Monthly Notices of the Royal Astronomical Society 508 (2), 2946-2963, 2021 | 31 | 2021 |
| Topology and geometry of the dark matter web: a multistream view NS Ramachandra, SF Shandarin Monthly Notices of the Royal Astronomical Society 467 (2), 1748-1762, 2017 | 18 | 2017 |
| From the inner to outer Milky Way: a photometric sample of 2.6 million red clump stars M Lucey, YS Ting, NS Ramachandra, K Hawkins Monthly Notices of the Royal Astronomical Society 495 (3), 3087-3103, 2020 | 15 | 2020 |
| Carbon-enhanced metal-poor star candidates from BP/RP spectra in Gaia DR3 M Lucey, N Al Kharusi, K Hawkins, YS Ting, N Ramachandra, ... Monthly Notices of the Royal Astronomical Society 523 (3), 4049-4066, 2023 | 12 | 2023 |
| Machine learning synthetic spectra for probabilistic redshift estimation: SYTH-Z N Ramachandra, J Chaves-Montero, A Alarcon, A Fadikar, S Habib, ... Monthly Notices of the Royal Astronomical Society 515 (2), 1927-1941, 2022 | 10 | 2022 |
| Differentiable predictions for large scale structure with shamnet AP Hearin, N Ramachandra, MR Becker, J DeRose arXiv preprint arXiv:2112.08423, 2021 | 10 | 2021 |
| A modular deep learning pipeline for galaxy-scale strong gravitational lens detection and modeling S Madireddy, N Ramachandra, N Li, J Butler, P Balaprakash, S Habib, ... arXiv preprint arXiv:1911.03867, 2019 | 9 | 2019 |
| Probabilistic neural networks for fluid flow model-order reduction and data recovery R Maulik, K Fukami, N Ramachandra, K Fukagata, K Taira arXiv preprint arXiv:2005.04271, 2020 | 8 | 2020 |
| Peculiar velocity estimation from kinetic SZ effect using deep neural networks Y Wang, N Ramachandra, EM Salazar-Canizales, HA Feldman, ... Monthly Notices of the Royal Astronomical Society 506 (1), 1427-1437, 2021 | 7 | 2021 |
| Dark matter haloes: a multistream view NS Ramachandra, SF Shandarin Monthly Notices of the Royal Astronomical Society 470 (3), 3359-3373, 2017 | 7 | 2017 |
| Neural network based point spread function deconvolution for astronomical applications H Wang, S Sreejith, Y Lin, N Ramachandra, A Slosar, S Yoo arXiv preprint arXiv:2210.01666, 2022 | 5 | 2022 |
| Interpretable Uncertainty Quantification in AI for HEP TY Chen, B Dey, A Ghosh, M Kagan, B Nord, N Ramachandra Argonne National Laboratory (ANL), Argonne, IL (United States); SLAC …, 2022 | 5 | 2022 |
