Paradigm shift for machine learning
Snorkel’s technology has been used to unlock new ML use cases in healthcare, criminology, and journalism and to power mission critical AI applications for Fortune 500 enterprises such as Chubb, Genentech, Google, and more.
Pioneering technology

SIGMOD
Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale - S. Bach, et al, 2019

NATURE COMMS
Weakly Supervised Classification of Aortic Valve Malformations Using Unlabeled Cardiac MRI Sequences - J. Fries, et al, 2019

SIGMOD
Data Programming With DDLite: Putting Humans in a Different Part of the Loop - H. Ehrenberg, et al, 2016

NEURIPS
Learning to Compose Domain-Specific Transformations for Data Augmentation - A. Ratner, et al, 2017

VLDB
Snorkel: Rapid Training Data Creation With Weak Supervision - Alexander Ratner, Stephen H Bach, Henry Ehrenberg, Jason Fries, Sen Wu, Christopher Ré
Research at Snorkel AI
Our research team works closely with partners in academia and industry to make data-centric AI ubiquitous. The Snorkel AI team regularly publishes in academic journals, contributes to open source projects, applies research to the Snorkel Flow platform, and is faculty at the world's leading educational institutions.
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