Piotr Teterwak
Piotr Teterwak
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Cited by
Cited by
Supervised contrastive learning
P Khosla*, P Teterwak*, C Wang, A Sarna, Y Tian, P Isola, A Maschinot, ...
NeurIPS 2020, 2020
Boundless: Generative adversarial networks for image extension
P Teterwak, A Sarna, D Krishnan, A Maschinot, D Belanger, C Liu, ...
2019 IEEE/CVF International Conference on Computer Vision (ICCV), 10520-10529, 2019
Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density
K Saito, D Kim, P Teterwak, S Sclaroff, T Darrell, K Saenko
ICCV 2021, 2021
Oconet: Image extrapolation by object completion
RS Bowen, H Chang, C Herrmann, P Teterwak, C Liu, R Zabih
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
VisDA-2021 Competition Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data
D Bashkirova, D Hendrycks, D Kim, S Mishra, K Saenko, K Saito, ...
NeurIPS Competition Track, 2021
Shared roots: Regularizing deep neural networks through multitask learning
P Teterwak
Understanding invariance via feedforward inversion of discriminatively trained classifiers
P Teterwak, C Zhang, D Krishnan, MC Mozer
International Conference on Machine Learning, 10225-10235, 2021
ERM++: An Improved Baseline for Domain Generalization
P Teterwak, K Saito, T Tsiligkaridis, K Saenko, BA Plummer
arXiv preprint arXiv:2304.01973, 2023
Visda 2022 challenge: Domain adaptation for industrial waste sorting
D Bashkirova, S Mishra, D Lteif, P Teterwak, D Kim, F Alladkani, J Akl, ...
NeurIPS 2022 Competition Track, 104-118, 2022
Image extension neural networks
MP Bonnevie, A Maschinot, A Sarna, S Bi, J Wang, MS Krainin, W Tong, ...
US Patent App. 17/438,687, 2022
MixtureGrowth: Growing Neural Networks by Recombining Learned Parameters
C Pham, P Teterwak, S Nelson, BA Plummer
arXiv preprint arXiv:2311.04251, 2023
Supervised Contrastive Learning with Multiple Positive Examples
D Krishnan, P Khosla, P Teterwak, AY Sarna, AJ Maschinot, C Liu, ...
US Patent App. 17/920,623, 2023
Mind the Backbone: Minimizing Backbone Distortion for Robust Object Detection
K Saito, D Kim, P Teterwak, R Feris, K Saenko
arXiv preprint arXiv:2303.14744, 2023
SuperWeight Ensembles: Automated Compositional Parameter Sharing Across Diverse Architechtures
P Teterwak, S Nelson, N Dryden, D Bashkirova, K Saenko, BA Plummer
NeurIPS 2021 Competition and Demonstration Track Revised Selected Papers
D Kiela, M Ciccone, B Caputo, A Kanervisto, S Milani, K Ramanauskas, ...
NeurIPS 2021 Competitions and Demonstrations Track, i-ii, 2022
Supervised contrastive learning with multiple positive examples
D Krishnan, P Khosla, P Teterwak, AY Sarna, AJ Maschinot, C Liu, ...
US Patent 11,347,975, 2022
Supervised Contrastive Learning-Supplementary Material
P Khosla, P Teterwak, C Wang, A Sarna, Y Tian, P Isola, A Maschinot, ...
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