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The Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs.

, , , , , , , and . CoRR, (2023)

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CWY Parametrization for Scalable Learning of Orthogonal and Stiefel Matrices., , , and . CoRR, (2020)Machine Learning Explainability for External Stakeholders, , , and . (2020)cite arxiv:2007.05408.Bucket Renormalization for Approximate Inference., , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 109-118. PMLR, (2018)Bethe Bounds and Approximating the Global Optimum., and . AISTATS, volume 31 of JMLR Workshop and Conference Proceedings, page 618-631. JMLR.org, (2013)Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning., , , and . AAAI, page 51-60. AAAI Press, (2018)Iterative Teaching by Data Hallucination., , , , , , , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 9892-9913. PMLR, (2023)Simplex Random Features., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 28864-28888. PMLR, (2023)Representational Alignment Supports Effective Machine Teaching., , , , , , , , , and 4 other author(s). CoRR, (2024)Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning., , , , , , and . IJCAI, page 4745-4753. ijcai.org, (2017)Physics-Based Decoding Improves Magnetic Resonance Fingerprinting., , , and . MICCAI (2), volume 14221 of Lecture Notes in Computer Science, page 446-456. Springer, (2023)