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De-novo Chemical Reaction Generation by Means of Temporal Convolutional Neural Networks. (arXiv:2310.17341v3 [cs.LG] UPDATED)
cs.LG updates on arXiv.org arxiv.org
We present here a combination of two networks, Recurrent Neural Networks
(RNN) and Temporarily Convolutional Neural Networks (TCN) in de novo reaction
generation using the novel Reaction Smiles-like representation of reactions
(CGRSmiles) with atom mapping directly incorporated. Recurrent Neural Networks
are known for their autoregressive properties and are frequently used in
language modelling with direct application to SMILES generation. The relatively
novel TCNs possess similar properties with wide receptive field while obeying
the causality required for natural language processing (NLP). …
arxiv combination convolutional neural networks mapping networks neural networks novel recurrent neural networks representation rnn temporal