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Quasar Classification Using Color and Variability

, , , , , , , , and . (2015)cite arxiv:1508.04121Comment: 32 pages, 23 figures. Accepted for publication in ApJS. Data file is available at http://oberon.physics.drexel.edu/~tinapeters/quasarclassification/Peters2015Catalog_30042015.fit.bz2.

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SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases., , , , , , , , , and 15 other author(s). CoRR, (2021)Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks., , , and . CoRR, (2021)Leveraging Abstract Meaning Representation for Knowledge Base Question Answering., , , , , , , , , and 20 other author(s). ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 3884-3894. Association for Computational Linguistics, (2021)Quasar Classification Using Color and Variability, , , , , , , , and . (2015)cite arxiv:1508.04121Comment: 32 pages, 23 figures. Accepted for publication in ApJS. Data file is available at http://oberon.physics.drexel.edu/~tinapeters/quasarclassification/Peters2015Catalog_30042015.fit.bz2.Logic Embeddings for Complex Query Answering., , , , , , and . CoRR, (2021)Question Answering over Knowledge Bases by Leveraging Semantic Parsing and Neuro-Symbolic Reasoning., , , , , , , , , and 20 other author(s). CoRR, (2020)Training Logical Neural Networks by Primal-Dual Methods for Neuro-Symbolic Reasoning., , , , , and . ICASSP, page 5559-5563. IEEE, (2021)Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks., , , and . AAAI, page 8212-8219. AAAI Press, (2022)Approximate Inference in Logical Credal Networks., , , , , , and . IJCAI, page 5694-5701. ijcai.org, (2023)SYGMA: A System for Generalizable and Modular Question Answering Over Knowledge Bases., , , , , , , , , and 15 other author(s). EMNLP (Findings), page 3866-3879. Association for Computational Linguistics, (2022)