Resources

Community

For broader Q&A, discussions about using Snorkel, tutorial requests, etc., we have a community forum on Spectrum.

Mailing List

Stay up-to-date about the latest Snorkel-related announcements, releases, and workshops with the mailing list. We promise not to clutter your inbox :)

GitHub Issues

We use GitHub Issues as a place to put bugs and feature requests — anything code-related.

GitHub

SNORKEL IN THE WILD

Applications

Serving >1B queries (multiple languages) with weak supervision and data slicing systems at Apple: Overton: A Data System for Monitoring and Improving Machine-Learned Products
Conversational agents at IBM: Bootstrapping Conversational Agents With Weak Supervision (AAAI 2019)
Web content & event classification at Google: Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale (SIGMOD Industry 2019), and Google AI blog post
Business intelligence at Intel: Osprey: Non-Programmer Weak Supervision of Imbalanced Extraction Problems (SIGMOD DEEM 2019)
Medical device surveillance with electronic health records Medical device surveillance with electronic health records
Anti-semitic tweet classification w/ Snorkel + transfer learning: A Technique for Building NLP Classifiers Efficiently with Transfer Learning and Weak Supervision (Blog post 2019)
Catching cheating at Chegg (Article)

Medical image triaging at Stanford Radiology: Cross-Modal Data Programming Enables Rapid Medical Machine Learning (Preprint)
GWAS KBC with Stanford Genomics: A machine-compiled database of genome-wide association studies (Nature Communications 2019)
Clinical text classification: A clinical text classification paradigm using weak supervision and deep representation (BMC MIDM 2019)
SwellShark: A Generative Model for Biomedical Named Entity Recognition without Labeled Data SwellShark: A Generative Model for Biomedical Named Entity Recognition without Labeled Data
Social media text mining: Deep Text Mining of Instagram Data without Strong Supervision (ICWI 2018)
Cardiac MRI classification with Stanford Medicine: Weakly supervised classification of rare aortic valve malformations (Nature Communications 2019)
Weak Supervision over Autonomous Driving Data with Intel: Utilizing Weak Supervision to Infer Complex Objects and Situations in Autonomous Driving Data (IEEE Intelligent Vehicles Symposium 2019)

PAPERS AND PRE-PRINTS

Publications

Snorkel: Rapid Training Data Creation with Weak Supervision (VLDB 2018)
Data Programming: Creating Large Training Sets, Quickly (NeurIPS 2016)
Snorkel and the Software 2.0 vision (KDD 2018)
Learning the Structure of Generative Models without Labeled Data (ICML 2017)
Learning Dependency Structures for Weak Supervision Models (ICML 2019)
Training Complex Models with Multi-Task Weak Supervision (AAAI 2019)
Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices (NeurIPS 2019)
The Role of Massively Multi-Task and Weak Supervision in Software 2.0 (CIDR 2019)
Snorkel: Fast Training Set Generation for Information Extraction (SIGMOD DEMO 2017)
Interactive Programmatic Labeling for Weak Supervision (KDD DCCL 2019)
Scene Graph Prediction with Limited Labels (ICCV 2019)

Learning to Compose Domain-Specific Transformations for Data Augmentation (NeurIPS 2017)
Inferring Generative Model Structure with Static Analysis (NeurIPS 2017)
Training Classifiers with Natural Language Explanations (ACL 2018)
Data Programming with DDLite: Putting Humans in a Different Part of the Loop (HILDA @ SIGMOD 2016; note Snorkel was previously DDLite)
Socratic Learning: Correcting Misspecified Generative Models using Discriminative Models
Fonduer: Knowledge Base Construction from Richly Formatted Data (SIGMOD 2018)
Snuba: Automating Weak Supervision to Label Training Data (VLDB 2019)
Improving Sample Complexity with Observational Supervision (ICLR LLD 2019)
A Kernel Theory of Modern Data Augmentation (ICML 2019)