Nesar Ramachandra
Nesar Ramachandra
Postdoctoral Candidate, Argonne National Laboratory
Dirección de correo verificada de anl.gov - Página principal
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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
1532018
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
522020
Multi-stream portrait of the cosmic web
NS Ramachandra, SF Shandarin
Monthly Notices of the Royal Astronomical Society 452 (2), 1643-1653, 2015
262015
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
232020
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
142017
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
42021
Global field reconstruction from sparse sensors with voronoi tessellation-assisted deep learning
K Fukami, R Maulik, N Ramachandra, K Fukagata, K Taira
arXiv preprint arXiv:2101.00554, 2021
42021
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
42020
Dark matter haloes: a multistream view
NS Ramachandra, SF Shandarin
Monthly Notices of the Royal Astronomical Society 470 (3), 3359-3373, 2017
42017
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
32020
Topology and geometry of the dark matter web
N Ramachandra, S Shandarin
APS April Meeting Abstracts 2017, M5. 003, 2017
32017
Modular Deep Learning Analysis of Galaxy-Scale Strong Lensing Images
S Madireddy, N Li, N Ramachandra, P Balaprakash, S Habib
ArXiv, 2019
22019
Beyond the hubble sequence–exploring galaxy morphology with unsupervised machine learning
TY Cheng, M Huertas-Company, CJ Conselice, A Aragón-Salamanca, ...
Monthly Notices of the Royal Astronomical Society 503 (3), 4446-4465, 2021
12021
Probabilistic neural network-based reduced-order surrogate for fluid flows
K Fukami, R Maulik, N Ramachandra, K Fukagata, K Taira
arXiv preprint arXiv:2012.08719, 2020
12020
Anomaly Detection in Astronomical Images with Generative Adversarial Networks
K Storey-Fisher, M Huertas-Company, N Ramachandra, F Lanusse, ...
arXiv preprint arXiv:2012.08082, 2020
12020
Matter power spectrum emulator for f (R) modified gravity cosmologies
N Ramachandra, G Valogiannis, M Ishak, K Heitmann
arXiv preprint arXiv:2010.00596, 2020
12020
A modular deep learning pipeline for galaxy-scale strong gravitational lens detection and modeling
S Madireddy, N Li, N Ramachandra, J Butler, P Balaprakash, S Habib, ...
arXiv preprint arXiv:1911.03867, 2019
12019
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
2021
Constraining Gravity with a -cut Cosmic Shear Analysis of the Hyper Suprime-Cam First-Year Data
L Vazsonyi, PL Taylor, G Valogiannis, NS Ramachandra, A Ferté, ...
arXiv preprint arXiv:2107.10277, 2021
2021
Anomaly detection in Hyper Suprime-Cam galaxy images with generative adversarial networks
K Storey-Fisher, M Huertas-Company, N Ramachandra, F Lanusse, ...
arXiv preprint arXiv:2105.02434, 2021
2021
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20