Shirley Ho
Affiliations: | Center for Computational Astrophysics | Flatiron Institute |
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| Hahn C, Eickenberg M, Ho S, et al. (2023) A forward modeling approach to analyzing galaxy clustering with SimBIG. Proceedings of the National Academy of Sciences of the United States of America. 120: e2218810120 |
| Wadekar D, Thiele L, Villaescusa-Navarro F, et al. (2023) Augmenting astrophysical scaling relations with machine learning: Application to reducing the Sunyaev-Zeldovich flux-mass scatter. Proceedings of the National Academy of Sciences of the United States of America. 120: e2202074120 |
| Jamieson D, Li Y, He S, et al. (2022) Simple lessons from complex learning: what a neural network model learns about cosmic structure formation. Pnas Nexus. 2: pgac250 |
| Cranmer M, Tamayo D, Rein H, et al. (2021) A Bayesian neural network predicts the dissolution of compact planetary systems. Proceedings of the National Academy of Sciences of the United States of America. 118 |
| Massara E, Villaescusa-Navarro F, Ho S, et al. (2021) Using the Marked Power Spectrum to Detect the Signature of Neutrinos in Large-Scale Structure. Physical Review Letters. 126: 011301 |
| Tamayo D, Cranmer M, Hadden S, et al. (2020) Predicting the long-term stability of compact multiplanet systems. Proceedings of the National Academy of Sciences of the United States of America |
| He S, Li Y, Feng Y, et al. (2019) Learning to predict the cosmological structure formation. Proceedings of the National Academy of Sciences of the United States of America |