DAVIS WERTHEIMER

Gates Hall 345
Cornell University
dww78-at cornell-dot edu

I'm a Ph.D. Candidate in the Cornell University Computer Science Department (Ithaca campus). My research interest is in Machine Learning and Computer Vision, with a focus on few-shot visual understanding. Since high-quality training data for a given task may not always be readily available, I believe it is important to understand how neural models generalize and adapt to new domains from partially relevant data or indirect supervision.

Bharath Hariharan is my advisor.

My resume can be found here.

Publications

Few-Shot Learning in Long-Tailed Settings
Davis Wertheimer, Luming Tang, Dhruv Baijal*, Pranjal Mittal*, Anika Talwar*, and Bharath Hariharan (* equal contribution)
An updated journal version of my CVPR'19 paper, currently under review
pdf code
Few-Shot Classification with Feature Map Reconstruction Networks
Davis Wertheimer*, Luming Tang* and Bharath Hariharan (* equal contribution)
CVPR 2021
arxiv pdf supp code video
Augmentation-Interpolative AutoEncoders for Unsupervised Few-Shot Image Generation
Davis Wertheimer, Omid Poursaeed and Bharath Hariharan
arxiv pdf supp
Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition
Luming Tang, Davis Wertheimer and Bharath Hariharan
CVPR 2020
arxiv pdf supp code video
Few-Shot Learning with Localization in Realistic Settings
Davis Wertheimer and Bharath Hariharan
CVPR 2019, oral
arxiv pdf supp code video

Education

Ph.D. candidate: Cornell University, Computer Science (current)
Undergrad: Stanford University, major in Symbolic Systems / minor in Mathematics

Misc

NeurIPS Outstanding Reviewer (2021)
ICCV Outstanding Reviewer (2021)
ICML Best Reviewer (2021)
CVPR Outstanding Reviewer (2021)
Anonymous peer reviewer for TPAMI (2021)
Anonymous peer reviewer for IJCV and TPAMI (2020)
TA for CS4780: Machine Learning for Intelligent Systems (2017)
TA for CS4786: Machine Learning for Data Scientists (2016)
Stanford graduate with distinction (3.9 GPA) (2016)
Member, Phi Beta Kappa (2016)
Intel Science Talent Search national semifinalist (2012)
Scholastic Art and Writing national gold key (2011)

Non-academic interests include fractal art, 3d printing jewelry, cooking, origami, and creating and making original ice cream and bread recipes. I also enjoy live art and music.

"Begin at the beginning, and go on till you
come to the end: then stop."
-Lewis Carroll

DAVIS WERTHEIMER
Gates Hall 345 Cornell University dww78-at cornell-dot edu	I'm a Ph.D. Candidate in the Cornell University Computer Science Department (Ithaca campus). My research interest is in Machine Learning and Computer Vision, with a focus on few-shot visual understanding. Since high-quality training data for a given task may not always be readily available, I believe it is important to understand how neural models generalize and adapt to new domains from partially relevant data or indirect supervision. Bharath Hariharan is my advisor. My resume can be found here.
Publications Few-Shot Learning in Long-Tailed Settings Davis Wertheimer, Luming Tang, Dhruv Baijal, Pranjal Mittal, Anika Talwar, and Bharath Hariharan ( equal contribution) An updated journal version of my CVPR'19 paper, currently under review pdf code Few-Shot Classification with Feature Map Reconstruction Networks Davis Wertheimer, Luming Tang and Bharath Hariharan (* equal contribution) CVPR 2021 arxiv pdf supp code video Augmentation-Interpolative AutoEncoders for Unsupervised Few-Shot Image Generation Davis Wertheimer, Omid Poursaeed and Bharath Hariharan arxiv pdf supp Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition Luming Tang, Davis Wertheimer and Bharath Hariharan CVPR 2020 arxiv pdf supp code video Few-Shot Learning with Localization in Realistic Settings Davis Wertheimer and Bharath Hariharan CVPR 2019, oral arxiv pdf supp code video
Education Ph.D. candidate: Cornell University, Computer Science (current) Undergrad: Stanford University, major in Symbolic Systems / minor in Mathematics
Misc NeurIPS Outstanding Reviewer (2021) ICCV Outstanding Reviewer (2021) ICML Best Reviewer (2021) CVPR Outstanding Reviewer (2021) Anonymous peer reviewer for TPAMI (2021) Anonymous peer reviewer for IJCV and TPAMI (2020) TA for CS4780: Machine Learning for Intelligent Systems (2017) TA for CS4786: Machine Learning for Data Scientists (2016) Stanford graduate with distinction (3.9 GPA) (2016) Member, Phi Beta Kappa (2016) Intel Science Talent Search national semifinalist (2012) Scholastic Art and Writing national gold key (2011) Non-academic interests include fractal art, 3d printing jewelry, cooking, origami, and creating and making original ice cream and bread recipes. I also enjoy live art and music.

"Begin at the beginning, and go on till you come to the end: then stop." -Lewis Carroll