| Scaling vision transformers to 22 billion parameters M Dehghani, J Djolonga, B Mustafa, P Padlewski, J Heek, J Gilmer, ... International Conference on Machine Learning, 7480-7512, 2023 | 604 | 2023 |
| Pali-x: On scaling up a multilingual vision and language model X Chen, J Djolonga, P Padlewski, B Mustafa, S Changpinyo, J Wu, ... arXiv preprint arXiv:2305.18565, 2023 | 183 | 2023 |
| PaliGemma: A versatile 3B VLM for transfer L Beyer, A Steiner, AS Pinto, A Kolesnikov, X Wang, D Salz, M Neumann, ... arXiv preprint arXiv:2407.07726, 2024 | 147 | 2024 |
| Revisiting neural scaling laws in language and vision IM Alabdulmohsin, B Neyshabur, X Zhai Advances in Neural Information Processing Systems 35, 22300-22312, 2022 | 110 | 2022 |
| Flexivit: One model for all patch sizes L Beyer, P Izmailov, A Kolesnikov, M Caron, S Kornblith, X Zhai, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 105 | 2023 |
| What do neural networks learn when trained with random labels? H Maennel*, IM Alabdulmohsin*, IO Tolstikhin, R Baldock, O Bousquet, ... Advances in Neural Information Processing Systems 33, 19693-19704, 2020 | 90 | 2020 |
| Patch n’pack: Navit, a vision transformer for any aspect ratio and resolution M Dehghani, B Mustafa, J Djolonga, J Heek, M Minderer, M Caron, ... Advances in Neural Information Processing Systems 36, 2023 | 88 | 2023 |
| PaLI-3 Vision Language Models: Smaller, Faster, Stronger X Chen, X Wang, L Beyer, A Kolesnikov, J Wu, P Voigtlaender, B Mustafa, ... arXiv preprint arXiv:2310.09199, 2023 | 86 | 2023 |
| Diagnosing failures of fairness transfer across distribution shift in real-world medical settings J Schrouff, N Harris, S Koyejo, IM Alabdulmohsin, E Schnider, ... Advances in Neural Information Processing Systems 35, 19304-19318, 2022 | 68 | 2022 |
| Adding Robustness to Support Vector Machines Against Adversarial Reverse Engineering IM Alabdulmohsin, X Gao, X Zhang Proceedings of the 23rd ACM International Conference on Conference on …, 2014 | 51 | 2014 |
| Getting vit in shape: Scaling laws for compute-optimal model design IM Alabdulmohsin, X Zhai, A Kolesnikov, L Beyer Advances in Neural Information Processing Systems 36, 2023 | 47 | 2023 |
| Maintaining fairness across distribution shift: do we have viable solutions for real-world applications J Schrouff, N Harris, O Koyejo, I Alabdulmohsin, E Schnider, ... arXiv preprint arXiv:2202.01034, 2022 | 45 | 2022 |
| Support vector machines with indefinite kernels. IM Alabdulmohsin, X Gao, X Zhang ACML, 2014 | 37 | 2014 |
| A near-optimal algorithm for debiasing trained machine learning models IM Alabdulmohsin, M Lucic Advances in Neural Information Processing Systems 34, 8072-8084, 2021 | 36* | 2021 |
| Efficient active learning of halfspaces via query synthesis I Alabdulmohsin, X Gao, X Zhang Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015 | 34 | 2015 |
| Algorithmic stability and uniform generalization IM Alabdulmohsin Advances in Neural Information Processing Systems, 19-27, 2015 | 27 | 2015 |
| The Impact of Reinitialization on Generalization in Convolutional Neural Networks I Alabdulmohsin, H Maennel, D Keysers arXiv preprint arXiv:2109.00267, 2021 | 24 | 2021 |
| Summability Calculus: A Comprehensive Theory of Fractional Finite Sums IM Alabdulmohsin Springer, 2018 | 19* | 2018 |
| Content-Agnostic Malware Detection in Heterogeneous Malicious Distribution Graph I Alabdulmohsin, YF Han, Y Shen, XL Zhang Proceedings of the 25th ACM International on Conference on Information and …, 2016 | 18 | 2016 |
| Large margin classification with indefinite similarities I Alabdulmohsin, M Cisse, X Gao, X Zhang Machine learning 103, 215-237, 2016 | 17 | 2016 |
Xiaohua ZhaiOpenAI, previously at Google DeepMind在 google.com 的电子邮件经过验证
