J
João Caldeira
Researcher at Fermilab
Publications - 19
Citations - 353
João Caldeira is an academic researcher from Fermilab. The author has contributed to research in topics: Test set & Cosmic microwave background. The author has an hindex of 9, co-authored 19 publications receiving 240 citations. Previous affiliations of João Caldeira include University of Chicago.
Papers
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Journal ArticleDOI
DeepCMB: Lensing reconstruction of the cosmic microwave background with deep neural networks
João Caldeira,João Caldeira,W. L. K. Wu,Brian Nord,Brian Nord,Camille Avestruz,Shubhendu Trivedi,K. T. Story +7 more
TL;DR: In this article, deep convolutional neural networks (CNNs) are used to reconstruct the CMB lensing potential with a high signal-to-noise ratio, reaching levels comparable to analytic approximations of MLE methods.
Journal ArticleDOI
DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks
TL;DR: In this paper, deep convolutional neural networks (CNNs) are used to reconstruct the CMB lensing potential with a high signal-to-noise ratio, reaching levels comparable to analytic approximations of MLE methods.
Journal ArticleDOI
Deeply Uncertain: Comparing Methods of Uncertainty Quantification in Deep Learning Algorithms
João Caldeira,Brian Nord +1 more
TL;DR: Three of the most common uncertainty quantification methods - Bayesian Neural Networks, Concrete Dropout, and Deep Ensembles - are compared to the standard analytic error propagation and made some recommendations for usage and interpretation of UQ methods.
Journal ArticleDOI
PT-symmetric quantum state discrimination.
Carl M. Bender,Dorje C. Brody,João Caldeira,Uwe Günther,Bernhard K. Meister,Boris F. Samsonov +5 more
TL;DR: In this paper, the formalism of quantum mechanics is explained and elucidated by applying it to a well-known problem in conventional Hermitian quantum mechanics, namely the problem of...
Posted Content
The Role of Machine Learning in the Next Decade of Cosmology
Michelle Ntampaka,Camille Avestruz,Steven Boada,João Caldeira,Jessi Cisewski-Kehe,Rosanne Di Stefano,Cora Dvorkin,August E. Evrard,Arya Farahi,D. P. Finkbeiner,Shy Genel,Alyssa A. Goodman,Andy D. Goulding,Shirley Ho,Arthur Kosowsky,Paul La Plante,François Lanusse,Michelle Lochner,Rachel Mandelbaum,Daisuke Nagai,Jeffrey A. Newman,Brian Nord,J. E. G. Peek,Austin Peel,Barnabás Póczos,Markus Michael Rau,Aneta Siemiginowska,Danica J. Sutherland,Hy Trac,Benjamin D. Wandelt +29 more
TL;DR: The next decade will bring new opportunities for data-driven cosmological discovery, but will also present new challenges for adopting ML methodologies and understanding the results.