Francisco Villaescusa-Navarro (@paco_astro) 's Twitter Profile
Francisco Villaescusa-Navarro

@paco_astro

Cosmologist in the morning, deep learner in the afternoon, and dreamer at night. Father all day. Quijote. CAMELS. Research Scientist @ Simons Foundation.

ID: 1424524891785674752

linkhttps://franciscovillaescusa.github.io calendar_today09-08-2021 00:16:29

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Cosmology from Home (@cosmofromhome) 's Twitter Profile Photo

Dear awesome people, we are excited to announce that the registration for Cosmology from Home 2023 is now open: cosmologyfromhome.com/registration/. Abstract submission deadline : 23 May 2023 at 23:59 UTC Registration closes by 30 June 2023. 1/ 😎🌌🏡📅

Elena Massara (@elenamassara) 's Twitter Profile Photo

🔍Worried about the presence of interlopers in your galaxy catalog? 📢We developed a new method based on GNNs to infer the interloper fraction in a catalog using likelihood-free inference. 📄 Check out our new paper: arxiv.org/abs/2309.05850

CAMELS project (@camels_project) 's Twitter Profile Photo

The newest ‘hump’ of the CAMELS project is live! We present and make publicly available 768 hydrodynamical zoomed-in simulations of massive halos varying 5 cosmological parameters and 23 astrophysical parameters within the IllustrisTNG model. Check out arxiv.org/abs/2403.10609

The newest ‘hump’ of the CAMELS project is live! We present and make publicly available 768 hydrodynamical zoomed-in simulations of massive halos varying 5 cosmological parameters and 23 astrophysical parameters within the IllustrisTNG model. Check out arxiv.org/abs/2403.10609
Georgios Valogiannis (@georgiosgv89) 's Twitter Profile Photo

Excited to share our latest paper, in collaboration with Francisco Villaescusa-Navarro and Marco Baldi! We perform the first application of the Wavelet Scattering Transform technique to test theories of gravity, finding very promising results! Arxiv link: arxiv.org/abs/2407.18647

Teresa Huang (@teresanhuang) 's Twitter Profile Photo

Can we advance cosmology via ML? Can we build better benchmarks for graph learning? Introducing CosmoBench: a large-scale cosmology benchmark for graph/geometric ML, with 34k clouds and 25k trees from SOTA simulations (2PB+ data, 41M+ core hours) Now accepted to NeurIPS Conference !