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Matthew D. Hoffman
Matthew D. Hoffman
Research Scientist, Google Research
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Stan: a probabilistic programming language
B Carpenter, A Gelman, M Hoffman, D Lee, B Goodrich, M Betancourt, ...
Journal of Statistical Software, 2015
80622015
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
56252014
Stochastic variational inference
MD Hoffman, DM Blei, C Wang, J Paisley
Journal of Machine Learning Research, 2013
31402013
Online learning for latent dirichlet allocation
M Hoffman, DM Blei, F Bach
Advances in Neural Information Processing Systems 23, 856-864, 2010
22992010
Variational autoencoders for collaborative filtering
D Liang, RG Krishnan, MD Hoffman, T Jebara
Proceedings of the 2018 World Wide Web Conference, 689-698, 2018
13682018
Music transformer
CZA Huang, A Vaswani, J Uszkoreit, N Shazeer, I Simon, C Hawthorne, ...
Advances in Neural Processing Systems 3, 4, 2018
9232018
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
7482022
Learning Activation Functions to Improve Deep Neural Networks
F Agostinelli, M Hoffman, P Sadowski, P Baldi
arXiv preprint arXiv:1412.6830, 2014
7222014
Stochastic Gradient Descent as Approximate Bayesian Inference
S Mandt, MD Hoffman, DM Blei
arXiv preprint arXiv:1704.04289, 2017
694*2017
Tensorflow distributions
JV Dillon, I Langmore, D Tran, E Brevdo, S Vasudevan, D Moore, B Patton, ...
arXiv preprint arXiv:1711.10604, 2017
6372017
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
4052016
What are Bayesian neural network posteriors really like?
P Izmailov, S Vikram, MD Hoffman, AGG Wilson
International conference on machine learning, 4629-4640, 2021
3992021
Deep Probabilistic Programming
D Tran, MD Hoffman, RA Saurous, E Brevdo, K Murphy, DM Blei
arXiv preprint arXiv:1701.03757, 2017
2382017
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
227*2014
Bayesian nonparametric matrix factorization for recorded music
M Hoffman, D Blei, P Cook
Proc. ICML, 439-446, 2010
2112010
Structured stochastic variational inference
MD Hoffman, DM Blei
Artificial Intelligence and Statistics, 2015
197*2015
Sparse stochastic inference for latent dirichlet allocation
D Mimno, M Hoffman, D Blei
arXiv preprint arXiv:1206.6425, 2012
1962012
Nonparametric variational inference
S Gershman, M Hoffman, D Blei
arXiv preprint arXiv:1206.4665, 2012
1892012
A variational analysis of stochastic gradient algorithms
S Mandt, M Hoffman, D Blei
International Conference on Machine Learning, 354-363, 2016
1712016
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
1672016
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