Tran, Dustin

Image transformer

Parmar, N., Vaswani, A., Uszkoreit, J., Kaiser, Ł., Shazeer, N., Ku, A., & Tran, D. (2018) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 1,085

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

Automatic differentiation variational inference

Kucukelbir, A., Tran, D., Ranganath, R., Gelman, A., & Blei, D. M. (2016) · arXiv

Gaussian Processes and Bayesian InferenceMarkov Chains and Monte Carlo Methods

Cited by 515

Simple and principled uncertainty estimation with deterministic deep learning via distance awareness

Liu, J. Z., Lin, Z., Padhy, S., Tran, D., Bedrax-Weiss, T., & Lakshminarayanan, B. (2020) · arXiv

Adversarial Robustness in Machine LearningGaussian Processes and Bayesian Inference

Cited by 237

Measuring Calibration in Deep Learning

Nixon, J., Dusenberry, M., Jerfel, G., Nguyen, T., Liu, J., Zhang, L., & Tran, D. (2019) · arXiv

Adversarial Robustness in Machine LearningAdvanced Neural Network Applications

Cited by 209

Revisiting the Calibration of Modern Neural Networks

Minderer, M., Djolonga, J., Romijnders, R., Hubis, F., Zhai, X., Houlsby, N., Tran, D., & Lucic, M. (2021) · arXiv

Adversarial Robustness in Machine LearningAdvanced Neural Network Applications

Cited by 160

Hyperparameter ensembles for robustness and uncertainty quantification

Wenzel, F., Snoek, J., Tran, D., & Jenatton, R. (2020) · arXiv

Machine Learning and Data ClassificationAdversarial Robustness in Machine Learning

Cited by 122

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

Larger language models do in-context learning differently

Wei, J., Wei, J., Tay, Y., Tran, D., Webson, A., Lu, Y., Chen, X., Liu, H., Huang, D., Zhou, D., et al. (2023) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 109

Long-form factuality in large language models

Wei, J., Yang, C., Song, X., Lu, Y., Hu, N., Huang, J., Tran, D., Peng, D., Liu, R., Huang, D., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 36

Combining Ensembles and Data Augmentation can Harm your Calibration

Wen, Y., Jerfel, G., Muller, R., Dusenberry, M. W., Snoek, J., Lakshminarayanan, B., & Tran, D. (2020) · arXiv

Adversarial Robustness in Machine LearningAdvanced Neural Network Applications

Cited by 27