1,335 research outputs found

    The Resurgence of the Highly Ylidic N‐Heterocyclic Olefins as a New Class of Organocatalysts

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    In recent decades, N‐heterocyclic carbenes have become established as a prevalent family of organocatalysts. N‐Heterocyclic olefins, the alkylidene derivatives of N‐heterocyclic carbenes, have recently also emerged as efficient promoters for CO2 fixation and polymerization reactions. Their extraordinarily strong Lewis/Brønsted basicity suggests great potential as a new class of organocatalysts for a broad range of reactions in synthetic chemistry.One carbon better: N‐Heterocyclic olefins, the alkylidene derivatives of the prevalent N‐heterocyclic carbenes, have recently emerged as efficient promoters for CO2 fixation and polymerization reactions. Their extraordinarily strong Lewis/Brønsted basicity suggests great potential as a new class of organocatalysts for a broad range of reactions in synthetic chemistry.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137526/1/chem201503575_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137526/2/chem201503575.pd

    A Cosine Similarity-based Method for Out-of-Distribution Detection

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    The ability to detect OOD data is a crucial aspect of practical machine learning applications. In this work, we show that cosine similarity between the test feature and the typical ID feature is a good indicator of OOD data. We propose Class Typical Matching (CTM), a post hoc OOD detection algorithm that uses a cosine similarity scoring function. Extensive experiments on multiple benchmarks show that CTM outperforms existing post hoc OOD detection methods.Comment: Accepted paper at ICML 2023 Workshop on Spurious Correlations, Invariance, and Stability. 10 pages (4 main + appendix
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