Synaptic, transcriptional and chromatin genes disrupted in autism S De Rubeis, X He, AP Goldberg, CS Poultney, K Samocha, ... Nature 515 (7526), 209-215, 2014 | 2660 | 2014 |
Patterns and rates of exonic de novo mutations in autism spectrum disorders BM Neale, Y Kou, L Liu, A Ma’Ayan, KE Samocha, A Sabo, CF Lin, ... Nature 485 (7397), 242-245, 2012 | 2000 | 2012 |
Likelihood-free cosmological inference with type Ia supernovae: approximate Bayesian computation for a complete treatment of uncertainty A Weyant, C Schafer, WM Wood-Vasey The Astrophysical Journal 764 (2), 116, 2013 | 126 | 2013 |
Computational design and performance of the Fast Ocean Atmosphere Model, version one R Jacob, C Schafer, I Foster, M Tobis, J Anderson Computational Science—ICCS 2001: International Conference San Francisco, CA …, 2001 | 103 | 2001 |
Semi-supervised learning for photometric supernova classification JW Richards, D Homrighausen, PE Freeman, CM Schafer, D Poznanski Monthly Notices of the Royal Astronomical Society 419 (2), 1121-1135, 2012 | 76 | 2012 |
Exploiting low-dimensional structure in astronomical spectra JW Richards, PE Freeman, AB Lee, CM Schafer The Astrophysical Journal 691 (1), 32, 2009 | 65 | 2009 |
Photometric redshift estimation using spectral connectivity analysis PE Freeman, JA Newman, AB Lee, JW Richards, CM Schafer Monthly Notices of the Royal Astronomical Society 398 (4), 2012-2021, 2009 | 60 | 2009 |
Exploring coupled atmosphere-ocean models using Vis5D WL Hibbard, J Anderson, I Foster, BE Paul, R Jacob, C Schafer, MK Tyree The International Journal of Supercomputer Applications and High Performance …, 1996 | 51 | 1996 |
Discovery with data: Leveraging statistics with computer science to transform science and society C Rudin, D Dunson, R Irizarry, H Ji, E Laber, J Leek, T McCormick, ... American Statistical Association White Paper, 2014 | 44 | 2014 |
How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics K Wang, YY Mao, AR Zentner, FC van den Bosch, JU Lange, CM Schafer, ... Monthly Notices of the Royal Astronomical Society 488 (3), 3541-3567, 2019 | 38 | 2019 |
High-dimensional density ratio estimation with extensions to approximate likelihood computation R Izbicki, A Lee, C Schafer Artificial intelligence and statistics, 420-429, 2014 | 38 | 2014 |
Accurate parameter estimation for star formation history in galaxies using SDSS spectra JW Richards, PE Freeman, AB Lee, CM Schafer Monthly Notices of the Royal Astronomical Society 399 (2), 1044-1057, 2009 | 35 | 2009 |
Likelihood-free inference in cosmology: Potential for the estimation of luminosity functions CM Schafer, PE Freeman Statistical Challenges in Modern Astronomy V, 3-19, 2012 | 29 | 2012 |
Constructing confidence regions of optimal expected size CM Schafer, PB Stark Journal of the American Statistical Association 104 (487), 1080-1089, 2009 | 29 | 2009 |
A statistical method for estimating luminosity functions using truncated data CM Schafer The Astrophysical Journal 661 (2), 703, 2007 | 26 | 2007 |
Maximizing science in the era of LSST: a community-based study of needed us capabilities J Najita, B Willman, DP Finkbeiner, RJ Foley, S Hawley, JA Newman, ... arXiv preprint arXiv:1610.01661, 2016 | 25 | 2016 |
High-dimensional density estimation via SCA: An example in the modelling of hurricane tracks SM Buchman, AB Lee, CM Schafer Statistical Methodology 8 (1), 18-30, 2011 | 24 | 2011 |
FOBOS: a next-generation spectroscopic facility K Bundy, K Westfall, N MacDonald, R Kupke, M Savage, C Poppett, ... Bulletin of the American Astronomical Society 51 (7), 198, 2019 | 18 | 2019 |
Whole exome sequencing reveals minimal differences between cell line and whole blood derived DNA CM Schafer, NG Campbell, G Cai, F Yu, V Makarov, S Yoon, MJ Daly, ... Genomics 102 (4), 270-277, 2013 | 15 | 2013 |
Fobos: A next-generation spectroscopic facility at the wm keck observatory K Bundy, K Westfall, N MacDonald, R Kupke, M Savage, C Poppett, ... arXiv preprint arXiv:1907.07195, 2019 | 13 | 2019 |