TC
Tom Charnock
astro-ph.COastro-ph.IMcs.LGstat.MLastro-ph.GAphysics.data-anhep-exhep-thphysics.comp-phstat.OT
On Valency
published · living versionsW_ntw4svwd·v1 · currentpublished
Preprints & journals
17 papers in the corpus · 2014–2024Hybrid summary statistics: neural weak lensing inference beyond the power spectrum2407.18909v1 · T. Lucas Makinen, Alan Heavens, Natalia Porqueres et al.2024 · 5 citationsarXiv
The Cosmic Graph: Optimal Information Extraction from Large-Scale Structure using Catalogues2207.05202v3 · T. Lucas Makinen, Tom Charnock, Pablo Lemos et al.2022 · 41 citationsarXiv
Lossless, Scalable Implicit Likelihood Inference for Cosmological Fields2107.07405v2 · T. Lucas Makinen, Tom Charnock, Justin Alsing et al.2021 · 46 citationsarXiv
Catalog-free modeling of galaxy types in deep images: Massive dimensional reduction with neural networks2102.01086v2 · Florian Livet, Tom Charnock, Damien Le Borgne et al.2021 · 9 citationsAstronomy & Astrophysics, Volume 652, id.A62, 23 pp. August 2021
Bayesian Neural Networks2006.01490v2 · Tom Charnock, Laurence Perreault-Levasseur, Francois Lanusse2020 · 28 citationsarXivon Valency
Detecting outliers in astronomical images with deep generative networks2003.08263v2 · Berta Margalef-Bentabol, Marc Huertas-Company, Tom Charnock et al.2020 · 56 citationsarXiv
Super-resolution emulator of cosmological simulations using deep physical models2001.05519v2 · Doogesh Kodi Ramanah, Tom Charnock, Francisco Villaescusa-Navarro et al.2020 · 70 citationsarXiv
Neural physical engines for inferring the halo mass distribution function1909.06379v1 · Tom Charnock, Guilhem Lavaux, Benjamin D. Wandelt et al.2019 · 26 citationsarXiv
The Quijote simulations1909.05273v2 · Francisco Villaescusa-Navarro, ChangHoon Hahn, Elena Massara et al.2019 · 354 citationsAPJS, 250, 2, (2020)
Painting halos from cosmic density fields of dark matter with physically motivated neural networks1903.10524v2 · Doogesh Kodi Ramanah, Tom Charnock, Guilhem Lavaux2019 · 40 citationsPhys. Rev. D 100, 043515 (2019)
Fast likelihood-free cosmology with neural density estimators and active learning1903.00007v1 · Justin Alsing, Tom Charnock, Stephen Feeney et al.2019 · 211 citationsarXiv
Towards online triggering for the radio detection of air showers using deep neural networks1809.01934v2 · Florian Fuhrer, Tom Charnock, Anne Zilles et al.2018 · 7 citationsarXiv
Automatic physical inference with information maximising neural networks1802.03537v3 · Tom Charnock, Guilhem Lavaux, Benjamin D. Wandelt2018 · 113 citationsPhys. Rev. D 97, 083004 (2018)
Planck confronts large scale structure: methods to quantify discordance1703.05959v1 · Tom Charnock, Richard A. Battye, Adam Moss2017 · 50 citationsPhys. Rev. D 95, 123535 (2017)
Deep Recurrent Neural Networks for Supernovae Classification1606.07442v2 · Tom Charnock, Adam Moss2016 · 123 citationsarXiv
CMB constraints on cosmic strings and superstrings1603.01275v2 · Tom Charnock, Anastasios Avgoustidis, Edmund J. Copeland et al.2016 · 135 citationsPhys. Rev. D 93, 123503 (2016)
Tension between the power spectrum of density perturbations measured on large and small scales1409.2769v1 · Richard A. Battye, Tom Charnock, Adam Moss2014 · 160 citationsPhys. Rev. D 91, 103508 (2015)
Career total: 27 works. 17 are in this corpus.
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