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Matthew D. Hoffman
Matthew D. Hoffman
Research Scientist, Google Research
google.com의 이메일 확인됨 - 홈페이지
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Stan: a probabilistic programming language
B Carpenter, A Gelman, M Hoffman, D Lee, B Goodrich, M Betancourt, ...
Journal of Statistical Software, 2015
77792015
The No-U-Turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo.
MD Hoffman, A Gelman
J. Mach. Learn. Res. 15 (1), 1593-1623, 2014
53862014
Stochastic variational inference
MD Hoffman, DM Blei, C Wang, J Paisley
Journal of Machine Learning Research, 2013
30472013
Online learning for latent dirichlet allocation
M Hoffman, DM Blei, F Bach
Advances in Neural Information Processing Systems 23, 856-864, 2010
22672010
Variational autoencoders for collaborative filtering
D Liang, RG Krishnan, MD Hoffman, T Jebara
Proceedings of the 2018 World Wide Web Conference, 689-698, 2018
12932018
Music transformer
CZA Huang, A Vaswani, J Uszkoreit, N Shazeer, I Simon, C Hawthorne, ...
Advances in Neural Processing Systems 3, 4, 2018
8602018
Underspecification presents challenges for credibility in modern machine learning
A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...
The Journal of Machine Learning Research 23 (1), 10237-10297, 2022
7132022
Learning Activation Functions to Improve Deep Neural Networks
F Agostinelli, M Hoffman, P Sadowski, P Baldi
arXiv preprint arXiv:1412.6830, 2014
6962014
Stochastic Gradient Descent as Approximate Bayesian Inference
S Mandt, MD Hoffman, DM Blei
arXiv preprint arXiv:1704.04289, 2017
679*2017
Tensorflow distributions
JV Dillon, I Langmore, D Tran, E Brevdo, S Vasudevan, D Moore, B Patton, ...
arXiv preprint arXiv:1711.10604, 2017
6152017
ELBO surgery: yet another way to carve up the variational evidence lower bound
MD Hoffman, MJ Johnson
NIPS 2016 Workshop on Advances in Approximate Bayesian Inference, 2016
3902016
What are Bayesian neural network posteriors really like?
P Izmailov, S Vikram, MD Hoffman, AGG Wilson
International conference on machine learning, 4629-4640, 2021
3662021
Deep Probabilistic Programming
D Tran, MD Hoffman, RA Saurous, E Brevdo, K Murphy, DM Blei
arXiv preprint arXiv:1701.03757, 2017
2362017
A Unified View of Static and Dynamic Source Separation Using Non-Negative Factorizations
P Smaragdis, C Févotte, GJ Mysore, N Mohammadiha, M Hoffman
IEEE Signal Processing Magazine, 2014
224*2014
Bayesian nonparametric matrix factorization for recorded music
M Hoffman, D Blei, P Cook
Proc. ICML, 439-446, 2010
2112010
Sparse stochastic inference for latent dirichlet allocation
D Mimno, M Hoffman, D Blei
arXiv preprint arXiv:1206.6425, 2012
1942012
Structured stochastic variational inference
MD Hoffman, DM Blei
Artificial Intelligence and Statistics, 2015
188*2015
Nonparametric variational inference
S Gershman, M Hoffman, D Blei
arXiv preprint arXiv:1206.4665, 2012
1862012
A variational analysis of stochastic gradient algorithms
S Mandt, M Hoffman, D Blei
International Conference on Machine Learning, 354-363, 2016
1702016
Patterns and Sequences: Interactive Exploration of Clickstreams to Understand Common Visitor Paths
Z Liu, Y Wang, M Dontcheva, M Hoffman, S Walker, A Wilson
IEEE Transactions on Visualization & Computer Graphics, 1-1, 2016
1622016
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