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polyBERT: A chemical language model to enable fully machine-driven ultrafast polymer informatics

Authors: Christopher Kuenneth; Rampi Ramprasad;

polyBERT: A chemical language model to enable fully machine-driven ultrafast polymer informatics

Abstract

This repository contains the code and data set of the polyBERT paper, which can be accessed on arXiv. polyBERT is a large chemical language machine learning model that has learned the PSMILES chemical language of polymers. It generates polymer fingerprints (PSMILES-based) quickly, facilitating rapid polymer informatics and machine-driven property predictions. polyBERT is compatible with GPUs and CPUs, and can easily scale on cloud systems.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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OpenAIRE UsageCountsViews provided by UsageCounts
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