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Discovering Symbolic Models from Deep Learning with Inductive Biases, , , , , , and . Advances in Neural Information Processing Systems, 33, page 17429--17442. Curran Associates, Inc., (2020)$Mangrove$: Learning Galaxy Properties from Merger Trees, , , , , and . (2022)cite arxiv:2210.13473Comment: 15 pages, 9 figures, 3 tables, 10 pages of Appendices. Accepted for publication in ApJ.Multiple physics pretraining for physical surrogate models, , , , , , , , , and 1 other author(s). arXiv preprint arXiv:2310.02994, (2023)Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks., , , , , , , and . CoRR, (2022)Mangrove: Learning Galaxy Properties from Merger Trees., , , , , and . CoRR, (2022)Automated discovery of interpretable gravitational-wave population models., and . CoRR, (2022)Augmenting astrophysical scaling relations with machine learning : application to reducing the SZ flux-mass scatter., , , , , , , , , and . CoRR, (2022)Symbolic Regression on FPGAs for Fast Machine Learning Inference., , , , , , , , , and . CoRR, (2023)AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models., , , , , , , , , and 4 other author(s). CoRR, (2023)Rediscovering orbital mechanics with machine learning., , , , and . Mach. Learn. Sci. Technol., 4 (4): 45002 (December 2023)