Dustin Tran
Dustin Tran
Research Scientist, Google
Verified email at google.com - Homepage
Cited by
Cited by
Image transformer
N Parmar, A Vaswani, J Uszkoreit, L Kaiser, N Shazeer, A Ku, D Tran
International Conference on Machine Learning, 4055-4064, 2018
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
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
Hierarchical variational models
R Ranganath, D Tran, D Blei
International Conference on Machine Learning, 324-333, 2016
Hierarchical implicit models and likelihood-free variational inference
D Tran, R Ranganath, DM Blei
arXiv preprint arXiv:1702.08896, 2017
Operator variational inference
R Ranganath, J Altosaar, D Tran, DM Blei
arXiv preprint arXiv:1610.09033, 2016
Deep probabilistic programming
D Tran, MD Hoffman, RA Saurous, E Brevdo, K Murphy, DM Blei
arXiv preprint arXiv:1701.03757, 2017
Tensorflow distributions
JV Dillon, I Langmore, D Tran, E Brevdo, S Vasudevan, D Moore, B Patton, ...
arXiv preprint arXiv:1711.10604, 2017
Variational Gaussian Process
D Tran, R Ranganath, DM Blei
arXiv preprint arXiv:1511.06499, 2015
Mesh-tensorflow: Deep learning for supercomputers
N Shazeer, Y Cheng, N Parmar, D Tran, A Vaswani, P Koanantakool, ...
arXiv preprint arXiv:1811.02084, 2018
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
Variational Inference via -Upper Bound Minimization
AB Dieng, D Tran, R Ranganath, J Paisley, DM Blei
arXiv preprint arXiv:1611.00328, 2016
Automatic differentiation variational inference
A Kucukelbir, D Tran, R Ranganath, A Gelman, DM Blei
arXiv preprint arXiv:1603.00788, 2016
Noise contrastive priors for functional uncertainty
D Hafner, D Tran, T Lillicrap, A Irpan, J Davidson
Uncertainty in Artificial Intelligence, 905-914, 2020
Copula variational inference
D Tran, DM Blei, EM Airoldi
Advances in Neural Information Processing Systems, 3550-3558, 2015
Towards stability and optimality in stochastic gradient descent
P Toulis, D Tran, EM Airoldi
Proceedings of the Nineteenth International Conference on Artificial …, 2015
Measuring Calibration in Deep Learning.
J Nixon, MW Dusenberry, L Zhang, G Jerfel, D Tran
CVPR Workshops 2 (7), 2019
Discrete flows: Invertible generative models of discrete data
D Tran, K Vafa, KK Agrawal, L Dinh, B Poole
arXiv preprint arXiv:1905.10347, 2019
Bayesian layers: A module for neural network uncertainty
D Tran, MW Dusenberry, M van der Wilk, D Hafner
arXiv preprint arXiv:1812.03973, 2018
Simple, distributed, and accelerated probabilistic programming
D Tran, M Hoffman, D Moore, C Suter, S Vasudevan, A Radul, M Johnson, ...
arXiv preprint arXiv:1811.02091, 2018
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