Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices
Vincent S Chen, Zhenzhen Weng, Alexander Ratner, Christopher Ré
In NeurIPS 2019.
[blog]
[slides]
[paper]
[code]
Scene Graph Prediction with Limited Labels
Vincent S Chen, Paroma Varma, Ranjay Krishna, Michael Bernstein, Christopher Ré, Li Fei-Fei
In ICCV 2019.
[paper]
[code]
[poster]
Powerful Abstractions for Programming Your Training Data
Sen Wu, Vincent S. Chen, Braden Hancock, Alex Ratner, Chris Ré, and other members of Hazy Lab
SuperGLUE Benchmark.
[blog]
[code]
Massive Multi-Task Learning: Bringing More Supervision to Bear
Braden Hancock, Clara McCreery, Ines Chami, Vincent S. Chen, Sen Wu, Jared Dunnmon, Paroma Varma, Max Lam, and Chris Ré
GLUE Benchmark.
[blog]
Weakly supervised classification of rare aortic valve malformations using unlabeled cardiac MRI sequences
Jason A Fries, Paroma Varma, Vincent S Chen, Ke Xiao, Heliodoro Tejeda, Priyanka Saha, Jared Dunnmon, Henry Chubb, Shiraz Maskatia, Madalina Fiterau, Scott Delp, Euan Ashley, Christopher Ré, James Priest
In Nature Communications 2019.
[paper]
[code]
Automated Training Set Generation for Aortic Valve Classification
Vincent Chen, Paroma Varma, Madalina Fiterau, James Priest and Christopher Ré.
Using weak-supervision, we learn probabilistic training labels for aortic valve MRIs.
In NeurIPS 2017, ML4H Workshop.
[poster]