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pocoMC: A Python package for accelerated Bayesian inference in astronomy and cosmology.

M. Karamanis, D. Nabergoj, F. Beutler, J. Peacock, and U. Seljak. J. Open Source Softw., 7 (79): 4634 (November 2022)

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Translation and Rotation Equivariant Normalizing Flow (TRENF) for Optimal Cosmological Analysis.B. Dai, and U. Seljak. CoRR, (2022)Confirmation of general relativity on large scales from weak lensing and galaxy velocitiesR. Reyes, R. Mandelbaum, U. Seljak, T. Baldauf, J. Gunn, L. Lombriser, and R. Smith. Nature, 7286 (464): 256--258 (March 2010)Unsupervised in-distribution anomaly detection of new physics through conditional density estimation.G. Stein, U. Seljak, and B. Dai. CoRR, (2020)A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series.G. Stein, U. Seljak, V. Böhm, G. Aldering, P. Antilogus, C. Aragon, S. Bailey, C. Baltay, S. Bongard, K. Boone and 30 other author(s). CoRR, (2022)Statistical Significance Testing for Mixed Priors: A Combined Bayesian and Frequentist Analysis.J. Robnik, and U. Seljak. Entropy, 24 (10): 1328 (2022)pocoMC: A Python package for accelerated Bayesian inference in astronomy and cosmology.M. Karamanis, D. Nabergoj, F. Beutler, J. Peacock, and U. Seljak. J. Open Source Softw., 7 (79): 4634 (November 2022)Deterministic Langevin Unconstrained Optimization with Normalizing Flows.J. Sullivan, and U. Seljak. CoRR, (2023)CosmicRIM : Reconstructing Early Universe by Combining Differentiable Simulations with Recurrent Inference MachinesC. Modi, F. Lanusse, U. Seljak, D. Spergel, and L. Perreault-Levasseur. (2021)cite arxiv:2104.12864Comment: Published as a workshop paper at ICLR 2021 SimDL Workshop.Generative Learning of Counterfactual for Synthetic Control Applications in Econometrics.C. Modi, and U. Seljak. CoRR, (2019)The Seventh Data Release of the Sloan Digital Sky SurveyK. Abazajian, J. Adelman-McCarthy, M. Agüeros, S. Allam, C. Prieto, D. An, K. Anderson, S. Anderson, J. Annis, N. Bahcall and 194 other author(s). The Astrophysical Journal Supplement Series, 182 (2): 543 (2009)

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pocoMC: A Python package for accelerated Bayesian inference in astronomy and cosmology.

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Disambiguation of "Seljak, Uros"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML pocoMC: A Python package for accelerated Bayesian inference in astronomy and cosmology.

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pocoMC: A Python package for accelerated Bayesian inference in astronomy and cosmology.