Shirley Ho
Astronomy and Astrophysics · 2008–2020
A researcher in the Science corpus: 50 papers; trusts 75 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Astronomy and Astrophysics — 1,458 citations into it; #2,577 of 10,964 by trust here, #351 by citations
- Instrumentation — 646 citations into it; #1,706 of 3,502 by trust here, #430 by citations
- Nuclear and High Energy Physics — 380 citations into it; #5,726 of 6,161 by trust here, #313 by citations
- Artificial Intelligence — 130 citations into it
- Statistical and Nonlinear Physics — 108 citations into it
- Computer Vision and Pattern Recognition — 74 citations into it
- AI for Physical Sciences — 22 citations into it
- Optimization & Training — 14 citations into it
Whom Shirley Ho trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Daniel J. Eisenstein
- H. Seo
- R. Scoccimarro
- M. White
- Martín Crocce
- David Schlegel
- Douglas P. Finkbeiner
- Diederik P. Kingma
- M. Blanton
- A. Lewis
Who trusts Shirley Ho overall
- D. Weinberg
- A. Ross
- M. Liguori
- Benjamin R. Granett
- M. Mortonson
- L. Senatore
- C. Chuang
- M. Kamionkowski
- E. Sefusatti
- F. Beutler
Papers from Shirley Ho's perspective
Ordered by how strongly the researchers Shirley Ho trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Spectroscopic Target Selection in the Sloan Digital Sky Survey: The Main Galaxy Sample
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Maps of Dust Infrared Emission for Use in Estimation of Reddening and Cosmic Microwave Background Radiation Foregrounds
Their papers
- Estimating Cosmological Parameters from the Dark Matter Distribution (2016) — 83 citations
- Learning Symbolic Physics with Graph Networks (2019) — 99 citations
- Fast Function to Function Regression (2014) — 31 citations
- Lagrangian Neural Networks (2020) — 615 citations
- Discovering Symbolic Models from Deep Learning with Inductive Biases (2020) — 676 citations
- The Simons Observatory (2019) — 342 citations
- The Wide Field Infrared Survey Telescope: 100 Hubbles for the 2020s (2019) — 140 citations
- The Quijote Simulations (2019) — 273 citations
- Learning to predict the cosmological structure formation (2018) — 192 citations
- CosmoFlow: Using Deep Learning to Learn the Universe at Scale (2018) — 138 citations
- Analysis of Cosmic Microwave Background with Deep Learning (2018) — 8 citations
- The Simons Observatory: science goals and forecasts (2018) — 1,430 citations
- Unveiling $ν$ secrets with cosmological data: neutrino masses and mass hierarchy (2017) — 326 citations
- The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: First measurement of baryon acoustic oscillations between redshift 0.8 and 2.2 (2017) — 370 citations
- Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe (2017) — 1,066 citations
- The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: observational systematics and baryon acoustic oscillations in the correlation function (2016) — 226 citations
- The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological analysis of the DR12 galaxy sample (2016) — 2,632 citations
- The DESI Experiment Part I: Science,Targeting, and Survey Design (2016) — 1,247 citations
- The Atacama Cosmology Telescope: two-season ACTPol spectra and parameters (2016) — 203 citations
- Improvement of cosmological neutrino mass bounds (2016) — 157 citations