no code implementations • 30 Oct 2023 • Jeff Shen, Peter Melchior
Machine learning techniques can automatically identify outliers in massive datasets, much faster and more reproducible than human inspection ever could.
1 code implementation • 24 Oct 2022 • Christian Kragh Jespersen, Miles Cranmer, Peter Melchior, Shirley Ho, Rachel S. Somerville, Austen Gabrielpillai
Efficiently mapping baryonic properties onto dark matter is a major challenge in astrophysics.
1 code implementation • 14 Mar 2022 • ChangHoon Hahn, Peter Melchior
In this work, we present an alternative scalable approach to rigorous Bayesian inference using Amortized Neural Posterior Estimation (ANPE).
1 code implementation • 27 Sep 2021 • Tianshu Wang, Peter Melchior
But many concrete allocation problems in the experimental and observational sciences cannot or should not be expressed in the form of linear objective functions.
1 code implementation • 17 Jun 2021 • Miles Cranmer, Peter Melchior, Brian Nord
We present an approach for maximizing a global utility function by learning how to allocate resources in an unsupervised way.
1 code implementation • 29 Oct 2020 • T. Lucas Makinen, Lachlan Lancaster, Francisco Villaescusa-Navarro, Peter Melchior, Shirley Ho, Laurence Perreault-Levasseur, David N. Spergel
We seek to remove foreground contaminants from 21cm intensity mapping observations.
no code implementations • 25 Feb 2020 • DES Collaboration, Tim Abbott, Michel Aguena, Alex Alarcon, Sahar Allam, Steve Allen, James Annis, Santiago Avila, David Bacon, Alberto Bermeo, Gary Bernstein, Emmanuel Bertin, Sunayana Bhargava, Sebastian Bocquet, David Brooks, Dillon Brout, Elizabeth Buckley-Geer, David Burke, Aurelio Carnero Rosell, Matias Carrasco Kind, Jorge Carretero, Francisco Javier Castander, Ross Cawthon, Chihway Chang, Xinyi Chen, Ami Choi, Matteo Costanzi, Martin Crocce, Luiz da Costa, Tamara Davis, Juan De Vicente, Joseph DeRose, Shantanu Desai, H. Thomas Diehl, Jörg Dietrich, Scott Dodelson, Peter Doel, Alex Drlica-Wagner, Kathleen Eckert, Tim Eifler, Jack Elvin-Poole, Juan Estrada, Spencer Everett, August Evrard, Arya Farahi, Ismael Ferrero, Brenna Flaugher, Pablo Fosalba, Josh Frieman, Juan Garcia-Bellido, Marco Gatti, Enrique Gaztanaga, David Gerdes, Tommaso Giannantonio, Paul Giles, Sebastian Grandis, Daniel Gruen, Robert Gruendl, Julia Gschwend, Gaston Gutierrez, Will Hartley, Samuel Hinton, Devon L. Hollowood, Klaus Honscheid, Ben Hoyle, Dragan Huterer, David James, Mike Jarvis, Tesla Jeltema, Margaret Johnson, Stephen Kent, Elisabeth Krause, Richard Kron, Kyler Kuehn, Nikolay Kuropatkin, Ofer Lahav, Ting Li, Christopher Lidman, Marcos Lima, Huan Lin, Niall MacCrann, Marcio Maia, Adam Mantz, Jennifer Marshall, Paul Martini, Julian Mayers, Peter Melchior, Juan Mena, Felipe Menanteau, Ramon Miquel, Joe Mohr, Robert Nichol, Brian Nord, Ricardo Ogando, Antonella Palmese, Francisco Paz-Chinchon, Andrés Plazas Malagón, Judit Prat, Markus Michael Rau, Kathy Romer, Aaron Roodman, Philip Rooney, Eduardo Rozo, Eli Rykoff, Masao Sako, Simon Samuroff, Carles Sanchez, Alexandro Saro, Vic Scarpine, Michael Schubnell, Daniel Scolnic, Santiago Serrano, Ignacio Sevilla, Erin Sheldon, J. Allyn Smith, Eric Suchyta, Molly Swanson, Gregory Tarle, Daniel Thomas, Chun-Hao To, Michael A. Troxel, Douglas Tucker, Tamas Norbert Varga, Anja von der Linden, Alistair Walker, Risa Wechsler, Jochen Weller, Reese Wilkinson, Hao-Yi Wu, Brian Yanny, Zhuowen Zhang, Joe Zuntz
We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset.
Cosmology and Nongalactic Astrophysics
no code implementations • 9 Dec 2019 • Francois Lanusse, Peter Melchior, Fred Moolekamp
We present a Bayesian machine learning architecture that combines a physically motivated parametrization and an analytic error model for the likelihood with a deep generative model providing a powerful data-driven prior for complex signals.
4 code implementations • 27 Feb 2018 • Peter Melchior, Fred Moolekamp, Maximilian Jerdee, Robert Armstrong, Ai-Lei Sun, James Bosch, Robert Lupton
We present the source separation framework SCARLET for multi-band images, which is based on a generalization of the Non-negative Matrix Factorization to alternative and several simultaneous constraints.
Instrumentation and Methods for Astrophysics
3 code implementations • 30 Aug 2017 • Fred Moolekamp, Peter Melchior
We introduce a generalization of the linearized Alternating Direction Method of Multipliers to optimize a real-valued function $f$ of multiple arguments with potentially multiple constraints $g_\circ$ on each of them.
1 code implementation • 17 Nov 2016 • Peter Melchior, Andy D. Goulding
We extend the common mixtures-of-Gaussians density estimation approach to account for a known sample incompleteness by simultaneous imputation from the current model.
Instrumentation and Methods for Astrophysics High Energy Astrophysical Phenomena Data Analysis, Statistics and Probability Methodology
1 code implementation • 29 Jul 2014 • Barnaby Rowe, Mike Jarvis, Rachel Mandelbaum, Gary M. Bernstein, James Bosch, Melanie Simet, Joshua E. Meyers, Tomasz Kacprzak, Reiko Nakajima, Joe Zuntz, Hironao Miyatake, Joerg P. Dietrich, Robert Armstrong, Peter Melchior, Mandeep S. S. Gill
GALSIM is a collaborative, open-source project aimed at providing an image simulation tool of enduring benefit to the astronomical community.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics 85-04
1 code implementation • 16 Dec 2010 • Rene Andrae, Tim Schulze-Hartung, Peter Melchior
Concerning nonlinear models, the number of degrees of freedom is unknown, i. e., it is not possible to compute the value of reduced chi-squared.
Instrumentation and Methods for Astrophysics Data Analysis, Statistics and Probability Methodology
1 code implementation • 5 Aug 2010 • Peter Melchior, Massimo Viola, Björn Malte Schäfer, Matthias Bartelmann
We introduce a novel method for weak-lensing measurements, which is based on a mathematically exact deconvolution of the moments of the apparent brightness distribution of galaxies from the telescope's PSF.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics