Mustafa, Basil
14 papers on CoChatORCID 0000-0001-7305-7890
Most cited papers
- Verified
Sigmoid Loss for Language Image Pre-Training
Zhai, X., Mustafa, B., Kolesnikov, A., & Beyer, L. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)
Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning
Cited by 1,127
- Verified
Gemini: A Family of Highly Capable Multimodal Models
Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv
Multimodal Machine Learning ApplicationsTopic Modeling
Cited by 990
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Big Self-Supervised Models Advance Medical Image Classification
Azizi, S., Mustafa, B., Ryan, F., Beaver, Z., Freyberg, J., Deaton, J., Loh, A., Karthikesalingam, A., Kornblith, S., Chen, T., et al. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Domain Adaptation and Few-Shot LearningArtificial Intelligence in Healthcare and Education
Cited by 685
- Verified
Towards Generalist Biomedical AI
Tu, T., Azizi, S., Driess, D., Schaekermann, M., Amin, M., Chang, P.-C., Carroll, A., Lau, C., Tanno, R., Ktena, I., et al. (2023) · arXiv
Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications
Cited by 483
- Verified
Towards Generalist Biomedical AI
Tu, T., Azizi, S., Driess, D., Schaekermann, M., Amin, M., Chang, P.-C., Carroll, A., Lau, C., Tanno, R., Ktena, I., et al. (2024) · NEJM AI
Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications
Cited by 483
- Verified
LiT: Zero-Shot Transfer with Locked-image text Tuning
Zhai, X., Wang, X., Mustafa, B., Steiner, A., Keysers, D., Kolesnikov, A., & Beyer, L. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning
Cited by 402
- Verified
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv
Multimodal Machine Learning ApplicationsTopic Modeling
Cited by 306
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Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging
Azizi, S., Culp, L., Freyberg, J., Mustafa, B., Baur, S., Kornblith, S., Chen, T., Tomasev, N., Mitrović, J., Strachan, P., et al. (2023) · Nature Biomedical Engineering
Domain Adaptation and Few-Shot LearningArtificial Intelligence in Healthcare and Education
Cited by 250
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Capabilities of Gemini Models in Medicine
Saab, K., Tu, T., Weng, W.-H., Tanno, R., Stutz, D., Wulczyn, E., Zhang, F., Strother, T., Park, C., Vedadi, E., et al. (2024) · arXiv
Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications
Cited by 117
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Scaling vision transformers to 22 billion parameters
Dehghani, M., Djolonga, J., Mustafa, B., Padlewski, P., Heek, J., Gilmer, J., Steiner, A., Caron, M., Geirhos, R., Alabdulmohsin, I., et al. (2023) · arXiv
Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning
Cited by 112
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Does your dermatology classifier know what it doesn’t know? Detecting the long-tail of unseen conditions
Guha Roy, A., Ren, J., Azizi, S., Loh, A., Natarajan, V., Mustafa, B., Pawlowski, N., Freyberg, J., Liu, Y., Beaver, Z., et al. (2022) · Medical Image Analysis
Anomaly Detection Techniques and ApplicationsCutaneous Melanoma Detection and Management
Cited by 77
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Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution
Dehghani, M., Mustafa, B., Djolonga, J., Heek, J., Minderer, M., Caron, M., Steiner, A., Puigcerver, J., Geirhos, R., Alabdulmohsin, I., et al. (2023) · arXiv
Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning
Cited by 45
- Verified
From Sparse to Soft Mixtures of Experts
Puigcerver, J., Riquelme, C., Mustafa, B., & Houlsby, N. (2023) · arXiv
Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning
Cited by 36
- Verified
SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
Tschannen, M., Gritsenko, A., Wang, X., Naeem, M. F., Alabdulmohsin, I., Parthasarathy, N., Evans, T., Beyer, L., Xia, Y., Mustafa, B., et al. (2025) · arXiv
Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications
Cited by 22
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