vincentsunnchen /blog vincentschen

vincent sunn chen

vincentsc [at] cs [dot] stanford [dot] edu

I'm a graduate student at Stanford with a concentration in machine learning and a minor in creative writing. I'm interested in shaping datasets to make deep learning more accesible to domain experts in fields like medical imaging.

I also love reading, writing, and photography!


Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices

Vincent S Chen, Zhenzhen Weng, Alexander Ratner, Christopher Ré

NeurIPS 2019.

Scene Graph Prediction with Limited Labels

Vincent S Chen, Paroma Varma, Ranjay Krishna, Michael Bernstein, Christopher Ré, Li Fei-Fei

ICCV 2019.

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 state-of-the-art, 06/15/2019

Massive Multi-Task Learning with Snorkel: 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 state-of-the-art, 03/22/2019

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

Nature Communications.

Automated Training Set Generation for Aortic Valve Classification

Vincent Chen, Paroma Varma, Madalina Fiterau, James Priest and Christopher Ré.

NeurIPS 2017, ML4H Workshop.

Using weak-supervision, we learn probabilistic training labels for aortic valve MRIs.


CS231N: Convolutional Neural Networks for Visual Recognition

Teaching Assistant, Spring 2018

Hosted office hours, advised student projects, and led discussion sections on backpropogation and weak supervision.