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Lessons Learned from Ariel Data Challenge 2022 - Inferring Physical Properties of Exoplanets From Next-Generation Telescopes., , , , , , , , , and 12 other author(s). NeurIPS (Competition and Demos), volume 220 of Proceedings of Machine Learning Research, page 1-17. PMLR, (2021)Reproducing Bayesian Posterior Distributions for Exoplanet Atmospheric Parameter Retrievals with a Machine Learning Surrogate Model., , , and . CoRR, (2023)A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks., , , , , , , , , and 1 other author(s). CoRR, (2023)Searching for Novel Chemistry in Exoplanetary Atmospheres using Machine Learning for Anomaly Detection., , , and . CoRR, (2023)Deep Learning Symmetries and Their Lie Groups, Algebras, and Subalgebras from First Principles., , , , , and . CoRR, (2023)A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks., , , , , , , , , and 1 other author(s). Axioms, 13 (3): 160 (March 2024)Identifying the Group-Theoretic Structure of Machine-Learned Symmetries., , , , , and . CoRR, (2023)Discovering Sparse Representations of Lie Groups with Machine Learning., , , , , and . CoRR, (2023)Z2 × Z2 Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks., , , , , , , , , and 1 other author(s). CoRR, (2023)ℤ2 × ℤ2 Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks., , , , , , , , , and 1 other author(s). Axioms, 13 (3): 188 (March 2024)