How to use graph neural networks to understand the Universe?
Talk, AstroGainz group meeting, Chile
Talk, How to use graph neural networks to understand the Universe?, Universidad Técnica Federico Santa María, Chile - Remote
Talks and presentations
The use of machine learning and artificial intelligence in astrophysics, cosmology, and gravitation researches
Talk, As astrocientistas: III Encontro Brasileiro de Meninas e Mulheres da Astrofísica, Gravitação e Cosmologia, Astrocientistas
Panelist, As astrocientistas: III Encontro Brasileiro de Meninas e Mulheres da Astrofísica, Gravitação e Cosmologia - Remote.
Cosmology with graph neural networks
Talk, SP Research Group meetings in Astro & Cosmo, Principia Institute
Talk, SP Research Group meetings in Astro & Cosmo – Principia Institute, São Paulo, Brazil
Graph neural networks for Cosmology
Talk, First Learning on Graphs (LOG) conference in South America, ICMC
Talk, First Learning on Graphs (LOG) conference in South America – ICMC, São Carlos, Brazil
Measuring the impact of systematics on the predictions of 𝛀m on simulated galaxy catalogs using graph neural networks
Talk, ML Session of DoA, Tsinghua University, Beijing, China
Virtual talk, ML Session of DoA, Tsinghua University, Beijing, China
Measuring the impact of systematics on the predictions of 𝛀m on simulated galaxy catalogs using graph neural networks
Talk, Yale Astronomy Data Science Seminar, Yale University, New Haven, CT, US
Virtual talk, Yale Astronomy Data Science Seminar, Yale
A proper probabilistic approach for halo-galaxy connection and likelihood-free parameter inference
Oral presentation, AI driven discovery in Physics and Astrophysics - CD3, UTokyo, UTokyo, Japan
Coordinates
The Influence of Systematics on Galaxy Catalogs - looking for a robust model to do field-level likelihood-free inference
Talk, Seminários do CBPF/COTEC, CBPF, Rio de Janeiro, Brazil
Talk, Seminários do CBPF/COTEC, CBPF, Rio de Janeiro, Brazil
Before real data: pressing graph neural networks to do field-level simulation-based inference with galaxies
Oral communication, ML-IAF/CCA-2023: Debating the potential of machine learning in astronomical surveys, CCA, New York, NY, US & IAP, Paris, France
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How to use Machine Learning (to try) to understand the Universe
Oral presentation, III mini-Workshop on the halo-galaxy connection for the South American community, Universidad de Atacama, Copiapó, Chile
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Cosmology from field-level likelihood-free inference: The first steps towards real data
Oral presentation, Pre-doc symposium , Flatiron Institute, New York, NY, US
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Field-level simulation-based inference: using GNNs to get a robust model
Talk, CITA cosmology discussion, University of Toronto, Toronto, Canada
Talk, CITA cosmology discussion, University of Toronto, Toronto, Canada
Cosmology from galaxy phase-space information and a bit of halo-galaxy connection
Talk, Grav Seminars, Gravitational Geometry and Dynamics research group, Aveiro, Portugal - Online
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Unraveling Cosmology from field-level likelihood-free inference - A robust model
Talk, Renoir Science Seminar, Recherche Energie NOIRe (RENOIR), Marseille, France
Talk, Renoir Science Seminar, Recherche Energie NOIRe (RENOIR), Marseille, France
Field-level likelihood-free inference with galaxies: a robust model
Talk, Cosmology Seminar KIPAC, Stanford University, Santa Clara County, CA, US
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Implicit likelihood inference using graph neural networks: a robust model to constrain 𝛀m
Talk, Data-Science X Astro seminar, Yale University
Talk, Data-Science X Astro seminar, Yale University, Yale University, New Haven, CT, US
A robust model to constrain 𝛀m with implicit likelihood free-inference
Talk, Open Group Seminars - Prof. Cora Dvorkin, Harvard University, Cambridge, MA, US
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Implicit likelihood inference: a robust model to constrain 𝛀m
Talk, Group Seminars - Prof. Bhuvnesh Jain, UPenn, Philadelphia, PA, US
Talk, Group Seminars - Prof. Bhuvnesh Jain, UPenn, Philadelphia, PA, US
Doing Cosmology with galaxies
Talk, Pizza Lunch Talks, Columbia University, New York, NY, US
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Simulation-based inference: constraining Ωm with galaxies phase-space information
Talkn, Tri-state Cosmology X Data Science Meeting, Flatiron Institute, New York, NY, US
Talk, Tri-state Cosmology X Data Science Meeting, Flatiron Institute
Using graph neural networks to constrain Ωm - A robust model
Talk, Cosmology Lunch Talks, Institute of Advanced Studies (IAS), Princeton, NJ, US
Talk, Cosmology Lunch Talks, Institute of Advanced Studies (IAS), Princeton, NJ, US
Constraining Ωm with phase-space information of galaxies
Oral presentation, KITP Conference: Galaxy Formation and Evolution in the Data Science Era, UC Santa Barbara, Santa Barbara, CA, US
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Can we use galaxies to constrain 𝛀m?
Talk, Journal club: Berkeley Cosmology Group, UC Berkeley, Berkeley, CA, US
Virtual talk, Journal club: Berkeley Cosmology Group, UC Berkeley, Berkeley, CA, US
Constraining Ωm using galaxies
Talk, Galaxy Formation Group Meeting, Flatiron Institute, New York, NY, US
Talk, Galaxy Formation Group Meeting, Flatiron Institute, New York, NY, US
Obtaining cosmological information through machine learning
Talk, Gothamfest 2023, Simons Foundation, New York, NY, US
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Halo-galaxy connection and machine learning: an aerial view
Oral presentation, II mini-Workshop on the halo-galaxy connection for the South American community, Universidad Técnica Federico Santa María, Santiago, Chile
Virtual presentation, II mini-Workshop on the halo-galaxy connection for the South American community, Universidad Técnica Federico Santa María, Santiago, Chile
Inferring cosmological parameters using galaxies
Oral presentation, CAMELS Workshop, Simons Foundation, New York, NY, US
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Graph neural networks for robust parameter inference in cosmology: the first steps before real data
Oral presentation, XLVI Reunião Anual da Sociedade Astronômica Brasileira, Planetário Rio, Rio de Janeiro, RJ, Brazil
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Obtaining cosmological covariance matrices with machine learning
Oral presentation, XLV Reunião Anual da Sociedade Astronômica Brasileira, Virtual participation
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Improving cosmological covariance matrices with machine learning
Talk, AI in Astronomy, IAG, USP, São Paulo, SP, Brazil
Virtual talk, AI in Astronomy, IAG, USP, São Paulo, SP, Brazil
Improving cosmological covariance matrices using machine learning
Talk, Journal Club: Astronomical Observatory of Trieste, I.N.A.F., Trieste, Italy
Virtual talk, Journal Club: Astronomical Observatory of Trieste, I.N.A.F., Trieste, Italy
A machine learning suite to mimic the halo-galaxy connection
International Conference - Poster presentation, International Conference on Machine Learning for Astrophysics - ML4Astro, Virtual participation - Catania, Italy
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Using machine learning to mimic the halo-galaxy connection
Talk, Group Meeting: Prof. Francesco Shankar, University of Southampton, Southampton, UK
Virtual talk, Group Meeting: Prof. Francesco Shankar, University of Southampton, Southampton, UK
First steps in the obtation of the cosmological parameters using denoised cosmological covariance matrices
Oral communication, Astrocientistas I: Encontro Brasileiro de Meninas e Mulheres da Astrofísica, Gravitação e Cosmologia, Virtual meeting
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Improving Covariance Matrices using Machine Learning
Meeting - Poster presentation, Latin American Workshop on Observational Cosmology, Virtual meeting
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Improving covariance matrices using machine learning
Oral poster presentation, Latin American Workshop on Observational Cosmology, International Centre for Theoretical Physics (ICTP) & South American Institute for Fundamental Research (SAIFR), São Paulo, SP, Brazil
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Observer dependence in the particle concept and the Unruh Effect
Poster presentation, XIII Semana de Física (XIII SeFís), Federal University of São Carlos, São Carlos, SP, Brazil
Poster presentation, XIII Semana de Física (XIII SeFís), Federal University of São Carlos, São Carlos, SP, Brazil
Regularization techniques in the Casimir effect
Poster presentation, V Semana Integrada do Instituto de Física de São Carlos (SIFSC 5), University of São Paulo, São Carlos, SP, Brazil
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Numerical studies on the classical and quantum harmonic oscillator
Poster presentation, IV Semana Integrada do Instituto de Física de São Carlos (SIFSC 4), University of São Paulo, São Carlos, SP, Brazil
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Synthesis and characterization of BaTi0.9Zr0.1O3 powders
Poster presentation, 20 Simpósio Internacional de Iniciação Científica (XX SIICUSP), University of São Paulo, São Paulo, SP, Brazil
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Development of a magnetic levitation system
Poster presentation, XIX Congresso de Iniciação Científica da UFSCar (XIX CIC), Federal University of São Carlos, São Carlos, SP, Brazil
Poster presentation, XIX Congresso de Iniciação Científica da UFSCar (XIX CIC), Federal University of São Carlos, São Carlos, SP, Brazil