( en | de | ru )

 

Disambiguation

From post

копироватьудалитьдобавить публикацию в буфер
The primordial magnetic field in our cosmic backyard

, , , , , , и . (2018)cite arxiv:1803.02629Comment: 14 pages, 19 figures. Revised version after peer review. Scientific and computational results are unchanged. This is an author-created, un-copyedited version of an article published in Classical and Quantum Gravity. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. This article is published under a CC BY licence.
DOI: 10.1088/1361-6382/aacde0

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

Torsten Enßlin

Torsten Andreas Enßlin

Klaus Enßlin

Wolfram Enßlin

Gerold Enßlin

 

Другие публикации лиц с тем же именем

Information field dynamics for simulation scheme construction. CoRR, (2012)HMCF - Hamiltonian Monte Carlo Sampling for Fields - A Python framework for HMC sampling with NIFTy, и . (2018)cite arxiv:1807.02709Comment: 36 pages, 4 figures, available at https://gitlab.mpcdf.mpg.de/ift/HMCF, see also arXiv:1708.01073.Radio Imaging with Information Field Theory., , , и . EUSIPCO, стр. 2683-2687. IEEE, (2018)Information Field Theory and Artificial Intelligence.. Entropy, 24 (3): 374 (2022)Bayesian Causal Inference, и . (2018)cite arxiv:1812.09895.Butterfly Transforms for Efficient Representation of Spatially Variant Point Spread Functions in Bayesian Imaging., , , , и . Entropy, 25 (4): 652 (апреля 2023)Signal inference with unknown response: calibration uncertainty renormalized estimator., , , , и . CoRR, (2014)D2O - a distributed data object for parallel high-performance computing in Python., , , и . CoRR, (2016)The primordial magnetic field in our cosmic backyard, , , , , , и . (2018)cite arxiv:1803.02629Comment: 14 pages, 19 figures. Revised version after peer review. Scientific and computational results are unchanged. This is an author-created, un-copyedited version of an article published in Classical and Quantum Gravity. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. This article is published under a CC BY licence.Probabilistic Autoencoder Using Fisher Information., , и . Entropy, 23 (12): 1640 (2021)