Michelle Ntampaka
Michelle Ntampaka
Verifierad e-postadress på cfa.harvard.edu - Startsida
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A machine learning approach for dynamical mass measurements of galaxy clusters
M Ntampaka, H Trac, DJ Sutherland, N Battaglia, B Póczos, J Schneider
The Astrophysical Journal 803 (2), 50, 2015
512015
Dynamical mass measurements of contaminated galaxy clusters using machine learning
M Ntampaka, H Trac, DJ Sutherland, S Fromenteau, B Póczos, ...
The Astrophysical Journal 831 (2), 135, 2016
422016
A first look at creating mock catalogs with machine learning techniques
X Xu, S Ho, H Trac, J Schneider, B Poczos, M Ntampaka
The Astrophysical Journal 772 (2), 147, 2013
212013
A Deep Learning Approach to Galaxy Cluster X-ray Masses
M Ntampaka, J ZuHone, D Eisenstein, D Nagai, A Vikhlinin, L Hernquist, ...
The Astrophysical Journal 876 (1), 82, 2019
142019
A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters
M Ho, MM Rau, M Ntampaka, A Farahi, H Trac, B Póczos
The Astrophysical Journal 887 (1), 25, 2019
102019
The Role of Machine Learning in the Next Decade of Cosmology
M Ntampaka, C Avestruz, S Boada, J Caldeira, J Cisewski-Kehe, ...
arXiv preprint arXiv:1902.10159, 2019
72019
Machine Learning Applied to the Reionization History of the Universe in the 21 cm Signal
P La Plante, M Ntampaka
The Astrophysical Journal 880 (2), 110, 2019
52019
The Velocity Distribution Function of Galaxy Clusters as a Cosmological Probe
M Ntampaka, H Trac, J Cisewski, LC Price
The Astrophysical Journal 835 (1), 106, 2017
42017
Using X-ray morphological parameters to strengthen galaxy cluster mass estimates via machine learning
SB Green, M Ntampaka, D Nagai, L Lovisari, K Dolag, D Eckert, ...
The Astrophysical Journal 884 (1), 33, 2019
32019
Cluster Cosmology with the Velocity Distribution Function of the HeCS-SZ Sample
M Ntampaka, K Rines, H Trac
The Astrophysical Journal 880 (2), 154, 2019
32019
The Next Decade of Astroinformatics and Astrostatistics
A Siemiginowska, M Kuhn, M Graham, AA Mahabal, SR Taylor
22019
A Hybrid Deep Learning Approach to Cosmological Constraints From Galaxy Redshift Surveys
M Ntampaka, DJ Eisenstein, S Yuan, LH Garrison
The Astrophysical Journal 889 (2), 151, 2020
12020
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era
B Nord, AJ Connolly, J Kinney, J Kubica, G Narayan, JEG Peek, ...
arXiv preprint arXiv:1911.02479, 2019
2019
Toward 1% calibration of CMB Lensing Cluster Mass Estimate with Deep Learning
S Nakoneczny, D Nagai, M Ntampaka, S Hassan, F Lanusse
2019
The Early Career Perspective on the Coming Decade, Astrophysics Career Paths, and the Decadal Survey Process
E Moravec, M Alpasian, A Amon, W Armentrout, G Arney, D Barron, ...
Bulletin of the American Astronomical Society 51 (7), 2019
2019
Increasing the Discovery Space in Astrophysics-A Collation of Six Submitted White Papers
G Fabbiano, M Elvis, A Accomazzi, GB Berriman, N Brickhouse, S Bose, ...
arXiv preprint arXiv:1903.06634, 2019
2019
Astro2020 Science White Paper: The Next Decade of Astroinformatics and Astrostatistics
A Siemiginowska, G Eadie, I Czekala, E Feigelson, EB Ford, V Kashyap, ...
arXiv preprint arXiv:1903.06796, 2019
2019
Using Machine Learning to Predict the Masses of Galaxy Clusters
N Mohamed-Hinds, M Ntampaka
American Astronomical Society Meeting Abstracts# 233 233, 2019
2019
Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Support Distribution Machines
M Ntampaka, H Trac, D Sutherland, S Fromenteau, B Poczos, J Schneider
American Astronomical Society Meeting Abstracts# 231 231, 2018
2018
Using Machine Learning to Populate Halos with Galaxies
X Xu, S Ho, M Ntampaka, B Poczos, J Schneider, H Trac
American Astronomical Society Meeting Abstracts# 221 221, 2013
2013
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Artiklar 1–20