Few-shot Adaptation to Distribution Shifts By Mixing Source and Target
Embeddings

Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings

23 May 2023

Ali Payani

Baharan Mirzasoleiman

Papers citing "Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings"

16 / 16 papers shown

Title
Change is Hard: A Closer Look at Subpopulation Shift Yuzhe Yang Haoran Zhang Dina Katabi Marzyeh Ghassemi OOD 26 99 0 23 Feb 2023
On Feature Learning in the Presence of Spurious Correlations Pavel Izmailov Polina Kirichenko Nate Gruver A. Wilson 66 126 0 20 Oct 2022
Test-Time Training with Masked Autoencoders Yossi Gandelsman Yu Sun Xinlei Chen Alexei A. Efros OOD 70 169 0 15 Sep 2022
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution Ananya Kumar Aditi Raghunathan Robbie Jones Tengyu Ma Percy Liang OODD 84 655 0 21 Feb 2022
Revisiting Weakly Supervised Pre-Training of Visual Perception Models Mannat Singh Laura Gustafson Aaron B. Adcock Vinicius de Freitas Reis B. Gedik Raj Prateek Kosaraju D. Mahajan Ross B. Girshick Piotr Dollár Laurens van der Maaten VLM 62 126 0 20 Jan 2022
BiaSwap: Removing dataset bias with bias-tailored swapping augmentation Eungyeup Kim Jihyeon Janel Lee Jaegul Choo 45 87 0 23 Aug 2021
Just Train Twice: Improving Group Robustness without Training Group Information Emmy Liu Behzad Haghgoo Annie S. Chen Aditi Raghunathan Pang Wei Koh Shiori Sagawa Percy Liang Chelsea Finn OOD 77 549 0 19 Jul 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization Damien Teney Ehsan Abbasnejad Simon Lucey Anton Van Den Hengel 70 88 0 12 May 2021
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 48 376 0 14 Oct 2020
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 51 1,217 0 20 Nov 2019
A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark Xiaohua Zhai J. Puigcerver Alexander Kolesnikov P. Ruyssen C. Riquelme ... Michael Tschannen Marcin Michalski Olivier Bousquet Sylvain Gelly N. Houlsby SSL 54 432 0 01 Oct 2019
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 494 10,466 0 12 Dec 2018
Do Better ImageNet Models Transfer Better? Simon Kornblith Jonathon Shlens Quoc V. Le OOD MLT 128 1,319 0 23 May 2018
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 326 9,418 0 28 May 2015
Deep Domain Confusion: Maximizing for Domain Invariance Eric Tzeng Judy Hoffman Ning Zhang Kate Saenko Trevor Darrell OOD 143 2,588 0 10 Dec 2014
How transferable are features in deep neural networks? J. Yosinski Jeff Clune Yoshua Bengio Hod Lipson OOD 115 8,309 0 06 Nov 2014