Gilmer, Justin

Sanity Checks for Saliency Maps

Adebayo, J., Gilmer, J., Muelly, M., Goodfellow, I., Hardt, M., & Kim, B. (2018) · arXiv

Explainable Artificial Intelligence (XAI)Visual Attention and Saliency Detection

Cited by 1,294

The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization

Hendrycks, D., Basart, S., Mu, N., Kadavath, S., Wang, F., Dorundo, E., Desai, R., Zhu, T., Parajuli, S., Guo, M., et al. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningAdversarial Robustness in Machine Learning

Cited by 1,250

Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)

Kim, B., Wattenberg, M., Gilmer, J., Cai, C., Wexler, J., Viegas, F., & Sayres, R. (2017) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 1,240

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

Adversarial Patch

Brown, T. B., Mané, D., Roy, A., Abadi, M., & Gilmer, J. (2017) · arXiv

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 509

SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability

Raghu, M., Gilmer, J., Yosinski, J., & Sohl-Dickstein, J. (2017) · arXiv

Explainable Artificial Intelligence (XAI)Neural Networks and Applications

Cited by 335

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

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

Adaptive Gradient Methods at the Edge of Stability

Cohen, J. M., Ghorbani, B., Krishnan, S., Agarwal, N., Medapati, S., Badura, M., Suo, D., Cardoze, D., Nado, Z., Dahl, G. E., et al. (2022) · arXiv

Stochastic Gradient Optimization TechniquesNeural Networks and Applications

Cited by 97

A mobile-optimized artificial intelligence system for gestational age and fetal malpresentation assessment

Gomes, R. G., Vwalika, B., Lee, C., Willis, A., Sieniek, M., Price, J. T., Chen, C., Kasaro, M. P., Taylor, J. A., Stringer, E. M., et al. (2022) · Communications Medicine

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 47

Small-scale proxies for large-scale Transformer training instabilities

Wortsman, M., Liu, P. J., Xiao, L., Everett, K., Alemi, A., Adlam, B., Co-Reyes, J. D., Gur, I., Kumar, A., Novak, R., et al. (2023) · arXiv

Stochastic Gradient Optimization TechniquesTopic Modeling

Cited by 5