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De-novo Chemical Reaction Generation by Means of Temporal Convolutional Neural Networks

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dc.contributor.authorBuin A
dc.contributor.authorChiang HY
dc.contributor.authorGadsden SA
dc.contributor.authorAlderson FA
dc.contributor.departmentMechanical Engineering
dc.date.accessioned2025-03-03T23:39:38Z
dc.date.available2025-03-03T23:39:38Z
dc.date.issued2023-10-26
dc.date.updated2025-03-03T23:39:37Z
dc.identifier.doihttps://doi.org/10.48550/arxiv.2310.17341
dc.identifier.urihttp://hdl.handle.net/11375/31373
dc.subject46 Information and Computing Sciences
dc.subject4611 Machine Learning
dc.subjectNetworking and Information Technology R&D (NITRD)
dc.subjectBioengineering
dc.subjectNeurosciences
dc.subjectMachine Learning and Artificial Intelligence
dc.subject1.1 Normal biological development and functioning
dc.titleDe-novo Chemical Reaction Generation by Means of Temporal Convolutional Neural Networks
dc.typeArticle

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