עקוב אחר
Dustin Tran
Dustin Tran
Research Scientist, Google
כתובת אימייל מאומתת בדומיין google.com - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
Image transformer‏
N Parmar, A Vaswani, J Uszkoreit, L Kaiser, N Shazeer, A Ku, D Tran‏
International Conference on Machine Learning, 4055-4064, 2018‏
19912018
Gemini: a family of highly capable multimodal models‏
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...‏
arXiv preprint arXiv:2312.11805, 2023‏
14902023
Automatic differentiation variational inference‏
A Kucukelbir, D Tran, R Ranganath, A Gelman, DM Blei‏
The Journal of Machine Learning Research 18 (1), 430-474, 2017‏
1145*2017
Tensorflow distributions‏
JV Dillon, I Langmore, D Tran, E Brevdo, S Vasudevan, D Moore, B Patton, ...‏
arXiv preprint arXiv:1711.10604, 2017‏
6462017
Tensor2tensor for neural machine translation‏
A Vaswani, S Bengio, E Brevdo, F Chollet, AN Gomez, S Gouws, L Jones, ...‏
arXiv preprint arXiv:1803.07416, 2018‏
6392018
Measuring Calibration in Deep Learning.‏
J Nixon, MW Dusenberry, L Zhang, G Jerfel, D Tran‏
CVPR workshops 2 (7), 2019‏
4782019
BatchEnsemble: An alternative approach to efficient ensemble and lifelong learning‏
Y Wen, D Tran, J Ba‏
International Conference on Learning Representations, 2020‏
4702020
Simple and principled uncertainty estimation with deterministic deep learning via distance awareness‏
J Liu, Z Lin, S Padhy, D Tran, T Bedrax Weiss, B Lakshminarayanan‏
Advances in neural information processing systems 33, 7498-7512, 2020‏
4612020
Mesh-TensorFlow: Deep learning for supercomputers‏
N Shazeer, Y Cheng, N Parmar, D Tran, A Vaswani, P Koanantakool, ...‏
Neural Information Processing Systems, 2018‏
4052018
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
3892023
Hierarchical variational models‏
R Ranganath, D Tran, D Blei‏
International conference on machine learning, 324-333, 2016‏
3872016
Flipout: Efficient pseudo-independent weight perturbations on mini-batches‏
Y Wen, P Vicol, J Ba, D Tran, R Grosse‏
arXiv preprint arXiv:1803.04386, 2018‏
3792018
Edward: A library for probabilistic modeling, inference, and criticism‏
D Tran, A Kucukelbir, AB Dieng, M Rudolph, D Liang, DM Blei‏
arXiv preprint arXiv:1610.09787, 2016‏
3692016
Operator variational inference‏
R Ranganath, D Tran, J Altosaar, D Blei‏
Advances in Neural Information Processing Systems 29, 2016‏
366*2016
Hierarchical implicit models and likelihood-free variational inference‏
D Tran, R Ranganath, DM Blei‏
Neural Information Processing Systems, 2017‏
361*2017
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context‏
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...‏
arXiv preprint arXiv:2403.05530, 2024‏
3582024
Revisiting the calibration of modern neural networks‏
M Minderer, J Djolonga, R Romijnders, F Hubis, X Zhai, N Houlsby, ...‏
Advances in Neural Information Processing Systems 34, 15682-15694, 2021‏
3062021
Deep probabilistic programming‏
D Tran, MD Hoffman, RA Saurous, E Brevdo, K Murphy, DM Blei‏
International Conference on Learning Representations, 2017‏
2412017
Hyperparameter ensembles for robustness and uncertainty quantification‏
F Wenzel, J Snoek, D Tran, R Jenatton‏
Advances in Neural Information Processing Systems 33, 6514-6527, 2020‏
2372020
Efficient and scalable Bayesian neural nets with rank-1 factors‏
M Dusenberry, G Jerfel, Y Wen, Y Ma, J Snoek, K Heller, ...‏
International Conference on Machine Learning, 2782-2792, 2020‏
2362020
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מאמרים 1–20