This profile is built from public research funding records (CIHR, NSERC and SSHRC) and PubMed. We have not imported them from a University of Toronto directory, so their courses and email address may be missing. Find their university profile.
Research
Latest papers
Expert surgeons and deep learning models can predict the outcome of surgical hemorrhage from 1 min of video.
Scientific reports · 2022
Utility of the Simulated Outcomes Following Carotid Artery Laceration Video Data Set for Machine Learning Applications.
JAMA network open · 2022
Latest funding
- $136,000
Inductive Biases in Deep Learning
NSERC · 2021 · Principal investigator
- $12,500
Inductive Biases in Deep Learning
NSERC · 2021 · Principal investigator
2 publications.
Expert surgeons and deep learning models can predict the outcome of surgical hemorrhage from 1 min of video.
Pangal DJ, Kugener G, Zhu Y, Sinha A, Unadkat V, Cote DJ, Strickland B, Rutkowski M, Hung A, Anandkumar A, Han XY, Papyan V, Wrobel B, Zada G, Donoho DA
Utility of the Simulated Outcomes Following Carotid Artery Laceration Video Data Set for Machine Learning Applications.
Kugener G, Pangal DJ, Cardinal T, Collet C, Lechtholz-Zey E, Lasky S, Sundaram S, Markarian N, Zhu Y, Roshannai A, Sinha A, Han XY, Papyan V, Hung A, Anandkumar A, Wrobel B, Zada G, Donoho DA
Inductive Biases in Deep Learning
Principal investigators: Papyan, Vardan
Keywords: neural networks; machine learning; deep learning; representation learning; classification; inductive bias; adversarial robustness; optimization; interpolation regime; sparse representations
Inductive Biases in Deep Learning
Principal investigators: Papyan, Vardan
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.