Biological Structure and Function Emerge from Scaling Unsupervised Learning to 250 Million Protein Sequences
bioRxiv, pp. 622803-31, 2019.
In the field of artificial intelligence, a combination of scale in data and model capacity enabled by unsupervised learning has led to major advances in representation learning and statistical generation. In biology, the anticipated growth of sequencing promises unprecedented data on natural sequence diversity. Learning the natural distri...More
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