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In machine learning, generalization against distribution shifts -- where deployment conditions diverge from the training scenarios -- is crucial, particularly in fields like climate modeling, biomedicine, and autonomous driving.
An overview of statistical learning theory
Vladimir N Vapnik · 1999
Earlier work this paper cites.
Challenges in combining projections from multiple climate models
Reto Knutti, Reinhard Furrer, Claudia Tebaldi, Jan Cermak, and Gerald A Meehl · 2010
Earlier work this paper cites.
Predicting the biodiversity response to climate change: challenges and advances
Christopher J Ellis · 2011
Earlier work this paper cites.
Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias
Chen Fang, Ye Xu, and Daniel N Rockmore · 2013
Earlier work this paper cites.
Domain generalization via invariant feature representation
Krikamol Muandet, David Balduzzi, and Bernhard Schölkopf · 2013
Earlier work this paper cites.
Climate extremes: challenges in estimating and understanding recent changes in the frequency and intensity of extreme climate and weather events
Francis W Zwiers, Lisa V Alexander, Gabriele C Hegerl, Thomas R Knutson, James P Kossin, Phillippe Naveau, Neville Nicholls, Christoph Schär, Sonia I Seneviratne, and Xuebin Zhang · 2013
Earlier work this paper cites.
Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 2015
Earlier work this paper cites.
Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
Earlier work this paper cites.
Deep coral: Correlation alignment for deep domain adaptation
Baochen Sun and Kate Saenko · 2016
Earlier work this paper cites.
Deeper, broader and artier domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales · 2017
Earlier work this paper cites.
Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, and Ronald M Summers · 2017
Earlier work this paper cites.
From detection of individual metastases to classification of lymph node status at the patient level: the camelyon17 challenge
Peter Bandi, Oscar Geessink, Quirine Manson, Marcory Van Dijk, Maschenka Balkenhol, Meyke Hermsen, Babak Ehteshami Bejnordi, Byungjae Lee, Kyunghyun Paeng, Aoxiao Zhong, et al · 2018
Earlier work this paper cites.
Recognition in terra incognita
Sara Beery, Grant Van Horn, and Pietro Perona · 2018
Earlier work this paper cites.
Functional map of the world
Gordon Christie, Neil Fendley, James Wilson, and Ryan Mukherjee · 2018
Earlier work this paper cites.
A unified feature disentangler for multi-domain image translation and manipulation
Alexander H Liu, Yen-Cheng Liu, Yu-Ying Yeh, and Yu-Chiang Frank Wang · 2018
Earlier work this paper cites.
Invariant models for causal transfer learning
Mateo Rojas-Carulla, Bernhard Schölkopf, Richard Turner, and Jonas Peters · 2018
Earlier work this paper cites.
The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
Philipp Tschandl, Cliff Rosendahl, and Harald Kittler · 2018
Earlier work this paper cites.
Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz · 2019
Earlier work this paper cites.
Objectnet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
Andrei Barbu, David Mayo, Julian Alverio, William Luo, Christopher Wang, Dan Gutfreund, Josh Tenenbaum, and Boris Katz · 2019
Earlier work this paper cites.
Structured domain randomization: Bridging the reality gap by context-aware synthetic data
Aayush Prakash, Shaad Boochoon, Mark Brophy, David Acuna, Eric Cameracci, Gavriel State, Omer Shapira, and Stan Birchfield · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Earlier work this paper cites.
Do imagenet classifiers generalize to imagenet?
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, and Vaishaal Shankar · 2019
Earlier work this paper cites.
Shiori Sagawa, Pang Wei Koh, Tatsunori B Hashimoto, and Percy Liang · 2019
Earlier work this paper cites.
Learning robust global representations by penalizing local predictive power
Haohan Wang, Songwei Ge, Zachary Lipton, and Eric P Xing · 2019
Earlier work this paper cites.
Domain randomization and pyramid consistency: Simulation-to-real generalization without accessing target domain data
Xiangyu Yue, Yang Zhang, Sicheng Zhao, Alberto Sangiovanni-Vincentelli, Kurt Keutzer, and Boqing Gong · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
In search of lost domain generalization
Ishaan Gulrajani and David Lopez-Paz · 2020
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Machine learning for financial risk management: a survey
Akib Mashrur, Wei Luo, Nayyar A Zaidi, and Antonio Robles-Kelly · 2020
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Learning to learn single domain generalization
Fengchun Qiao, Long Zhao, and Xi Peng · 2020
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Measuring domain shift for deep learning in histopathology
Karin Stacke, Gabriel Eilertsen, Jonas Unger, and Claes Lundström · 2020
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Adversarial domain adaptation with domain mixup
Minghao Xu, Jian Zhang, Bingbing Ni, Teng Li, Chengjie Wang, Qi Tian, and Wenjun Zhang · 2020
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The iwildcam 2021 competition dataset
Sara Beery, Arushi Agarwal, Elijah Cole, and Vighnesh Birodkar · 2021
Fine-tuning can distort pretrained features and underperform out-of-distribution
Ananya Kumar, Aditi Raghunathan, Robbie Matthew Jones, Tengyu Ma, and Percy Liang · 2022
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Surgical fine-tuning improves adaptation to distribution shifts
Yoonho Lee, Annie S Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, and Chelsea Finn · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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Diverse weight averaging for out-of-distribution generalization
Alexandre Rame, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, and Matthieu Cord · 2022
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Confidence-driven weighted retraining for predicting safety-critical failures in autonomous driving systems
Andrea Stocco and Paolo Tonella · 2022
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Domain generalization by marginal transfer learning
Gilles Blanchard, Aniket Anand Deshmukh, Ürun Dogan, Gyemin Lee, and Clayton Scott · 2021
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Exploiting domain-specific features to enhance domain generalization
Manh-Ha Bui, Toan Tran, Anh Tran, and Dinh Phung · 2021
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Swad: Domain generalization by seeking flat minima
Junbum Cha, Sanghyuk Chun, Kyungjae Lee, Han-Cheol Cho, Seunghyun Park, Yunsung Lee, and Sungrae Park · 2021
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A causal framework for distribution generalization
Rune Christiansen, Niklas Pfister, Martin Emil Jakobsen, Nicola Gnecco, and Jonas Peters · 2021
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Few-shot learning via learning the representation, provably
Simon Shaolei Du, Wei Hu, Sham M. Kakade, Jason D. Lee, and Qi Lei · 2021
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Perspectives in machine learning for wildlife conservation
Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R Costelloe, Silvia Zuffi, Benjamin Risse, Alexander Mathis, Mackenzie W Mathis, Frank van Langevelde, Tilo Burghardt, et al · 2022
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A fine-grained analysis on distribution shift
Olivia Wiles, Sven Gowal, Florian Stimberg, Sylvestre-Alvise Rebuffi, Ira Ktena, Krishnamurthy Dj Dvijotham, and Ali Taylan Cemgil · 2022
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Delving deep into the generalization of vision transformers under distribution shifts
Chongzhi Zhang, Mingyuan Zhang, Shanghang Zhang, Daisheng Jin, Qiang Zhou, Zhongang Cai, Haiyu Zhao, Xianglong Liu, and Ziwei Liu · 2022
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A closer look at in-context learning under distribution shifts
Kartik Ahuja and David Lopez-Paz · 2023
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Foundational models defining a new era in vision: A survey and outlook
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Machine and deep learning for longitudinal biomedical data: a review of methods and applications
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Drugood: Out-of-distribution dataset curator and benchmark for ai-aided drug discovery–a focus on affinity prediction problems with noise annotations
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Mm-vid: Advancing video understanding with gpt-4v (ision)
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Gpt-4v(ision) system card
OpenAI · 2023
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Model ratatouille: Recycling diverse models for out-of-distribution generalization, 2023
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Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al · 2023
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Erm++: An improved baseline for domain generalization
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How many unicorns are in this image? a safety evaluation benchmark for vision llms
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Adding conditional control to text-to-image diffusion models
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Large language models are good prompt learners for low-shot image classification, 2023
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