activity
20092021
most citedScikit-learn: Machine Learning in Python

63.6k citations · 75.8k across the 24 of their papers we have counts for

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Showing 2009Show all

5 papers · 1 filter

astro-ph.IM2009★ 924 cited

LSST Science Book, Version 2.0

LSST Science Collaboration, Paul A. Abell, Julius Allison +245

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade.…

astro-ph.CO2009★ 183 cited

First-Year Sloan Digital Sky Survey-II (SDSS-II) Supernova Results: Constraints on Non-Standard Cosmological Models

J. Sollerman, E. Mörtsell, T. M. Davis +18

We use the new SNe Ia discovered by the SDSS-II Supernova Survey together with additional supernova datasets as well as observations of the cosmic microwave background and baryon a…

astro-ph.CO2009★ 323 cited

SNANA: A Public Software Package for Supernova Analysis

Richard Kessler, Joseph P. Bernstein, David Cinabro +8

We describe a general analysis package for supernova (SN) light curves, called SNANA, that contains a simulation, light curve fitter, and cosmology fitter. The software is designed…

astro-ph.CO2009★ 696 cited

First-year Sloan Digital Sky Survey-II (SDSS-II) Supernova Results: Hubble Diagram and Cosmological Parameters

Richard Kessler, Andrew Becker, David Cinabro +43

We present measurements of the Hubble diagram for 103 Type Ia supernovae (SNe) with redshifts 0.04 < z < 0.42, discovered during the first season (Fall 2005) of the Sloan Digital S…

astro-ph.IM2009★ 57 cited

Reducing the Dimensionality of Data: Locally Linear Embedding of Sloan Galaxy Spectra

J. T. VanderPlas, A. J. Connolly

We introduce Locally Linear Embedding (LLE) to the astronomical community as a new classification technique, using SDSS spectra as an example data set. LLE is a nonlinear dimension…