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QuasarNet: A new research platform for the data-driven investigation of black holes

, , , , , , , , и . (2021)cite arxiv:2103.13932Comment: Main paper: 19 pages and 5 figures; Supplementary Materials: 10 pages and 5 figures, Submitted to Nature Astronomy.

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Rolf-Walter Briant

Benoît Briand

Manfred Nord

Kurt Nord

Antonie Nord

 

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CMB-S4: Forecasting Constraints on Primordial Gravitational Waves, , , , , , , , , и 227 other автор(ы). (2020)cite arxiv:2008.12619Comment: 24 pages, 8 figures, 9 tables, submitted to ApJ. arXiv admin note: text overlap with arXiv:1907.04473.DeepMerge: Classifying High-redshift Merging Galaxies with Deep Neural Networks., , , и . CoRR, (2020)Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference, , , , , , и . (2022)cite arxiv:2211.05836Comment: Accepted to the Workshop on Machine Learning and the Physical Sciences at the 36th Conference on Neural Information Processing Systems 2022 (NeurIPS 2022).Unsupervised Resource Allocation with Graph Neural Networks., , и . CoRR, (2021)Deep learning insights into cosmological structure formation., , , , и . CoRR, (2020)Deeply uncertain: comparing methods of uncertainty quantification in deep learning algorithms., и . Mach. Learn. Sci. Technol., 2 (1): 15002 (2021)Unsupervised Resource Allocation with Graph Neural Networks., , и . Preregister@NeurIPS, том 148 из Proceedings of Machine Learning Research, стр. 272-284. PMLR, (2020)Interpretable Uncertainty Quantification in AI for HEP., , , , , и . CoRR, (2022)DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks., , , , , и . CoRR, (2018)Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers., , , , , , , , , и 12 other автор(ы). CoRR, (2023)