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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
73002015
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
50132014
Stochastic variational inference
MD Hoffman, DM Blei, C Wang, J Paisley
Journal of Machine Learning Research, 2013
29392013
Online learning for latent dirichlet allocation
M Hoffman, DM Blei, F Bach
Advances in Neural Information Processing Systems 23, 856-864, 2010
22112010
Variational autoencoders for collaborative filtering
D Liang, RG Krishnan, MD Hoffman, T Jebara
Proceedings of the 2018 World Wide Web Conference, 689-698, 2018
11422018
Music transformer
CZA Huang, A Vaswani, J Uszkoreit, N Shazeer, I Simon, C Hawthorne, ...
Advances in Neural Processing Systems 3, 4, 2018
7832018
Learning Activation Functions to Improve Deep Neural Networks
F Agostinelli, M Hoffman, P Sadowski, P Baldi
arXiv preprint arXiv:1412.6830, 2014
6722014
Stochastic Gradient Descent as Approximate Bayesian Inference
S Mandt, MD Hoffman, DM Blei
arXiv preprint arXiv:1704.04289, 2017
642*2017
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
6182022
Tensorflow distributions
JV Dillon, I Langmore, D Tran, E Brevdo, S Vasudevan, D Moore, B Patton, ...
arXiv preprint arXiv:1711.10604, 2017
5402017
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
3682016
What are Bayesian neural network posteriors really like?
P Izmailov, S Vikram, MD Hoffman, AGG Wilson
International conference on machine learning, 4629-4640, 2021
2972021
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
219*2014
Bayesian nonparametric matrix factorization for recorded music
M Hoffman, D Blei, P Cook
Proc. ICML, 439-446, 2010
2102010
Sparse stochastic inference for latent dirichlet allocation
D Mimno, M Hoffman, D Blei
arXiv preprint arXiv:1206.6425, 2012
1942012
Nonparametric variational inference
S Gershman, M Hoffman, D Blei
arXiv preprint arXiv:1206.4665, 2012
1832012
Structured stochastic variational inference
MD Hoffman, DM Blei
Artificial Intelligence and Statistics, 2015
182*2015
A variational analysis of stochastic gradient algorithms
S Mandt, M Hoffman, D Blei
International Conference on Machine Learning, 354-363, 2016
1602016
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
1502016
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