Supervised contrastive learning P Khosla*, P Teterwak*, C Wang, A Sarna, Y Tian, P Isola, A Maschinot, ... NeurIPS 2020, 2020 | 4231 | 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 | 125* | 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 | 40 | 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 | 20 | 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 | 15 | 2021 |
Shared roots: Regularizing deep neural networks through multitask learning P Teterwak | 11* | 2014 |
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 | 7 | 2021 |
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 | 4 | 2022 |
Erm++: An improved baseline for domain generalization P Teterwak, K Saito, T Tsiligkaridis, K Saenko, BA Plummer arXiv preprint arXiv:2304.01973, 2023 | 3 | 2023 |
Learning to compose superweights for neural parameter allocation search P Teterwak, S Nelson, N Dryden, D Bashkirova, K Saenko, BA Plummer Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 2 | 2024 |
MixtureGrowth: Growing Neural Networks by Recombining Learned Parameters C Pham, P Teterwak, S Nelson, BA Plummer Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 1 | 2024 |
CLAMP: Contrastive LAnguage Model Prompt-tuning P Teterwak, X Sun, BA Plummer, K Saenko, SN Lim arXiv preprint arXiv:2312.01629, 2023 | 1 | 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 | 1 | 2023 |
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 | 1 | 2022 |
SLANT: Spurious Logo ANalysis Toolkit M Qraitem, P Teterwak, K Saenko, BA Plummer arXiv preprint arXiv:2406.01449, 2024 | | 2024 |
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 | | 2023 |
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 | | 2022 |
Learning to Compose SuperWeights for Neural Parameter Allocation Search Supplementary P Teterwak, S Nelson, N Dryden, D Bashkirova, K Saenko, BA Plummer | | |
MixtureGrowth: Growing Neural Networks by Recombining Learned Parameters Supplementary C Pham, P Teterwak, S Nelson, BA Plummer | | |
Supervised Contrastive Learning-Supplementary Material P Khosla, P Teterwak, C Wang, A Sarna, Y Tian, P Isola, A Maschinot, ... | | |