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Matthew D. Hoffman
Matthew D. Hoffman
Research Scientist, Google Research
E-mailová adresa ověřena na: google.com - Domovská stránka
Název
Citace
Citace
Rok
Stan: a probabilistic programming language
B Carpenter, A Gelman, M Hoffman, D Lee, B Goodrich, M Betancourt, ...
Journal of Statistical Software, 2015
62842015
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
41142014
Stochastic variational inference
MD Hoffman, DM Blei, C Wang, J Paisley
Journal of Machine Learning Research, 2013
26342013
Online learning for latent dirichlet allocation
M Hoffman, DM Blei, F Bach
Advances in Neural Information Processing Systems 23, 856-864, 2010
20532010
Variational autoencoders for collaborative filtering
D Liang, RG Krishnan, MD Hoffman, T Jebara
Proceedings of the 2018 World Wide Web Conference, 689-698, 2018
8452018
Learning Activation Functions to Improve Deep Neural Networks
F Agostinelli, M Hoffman, P Sadowski, P Baldi
arXiv preprint arXiv:1412.6830, 2014
5672014
Music transformer
CZA Huang, A Vaswani, J Uszkoreit, N Shazeer, I Simon, C Hawthorne, ...
Advances in Neural Processing Systems 3, 4, 2018
5632018
Stochastic Gradient Descent as Approximate Bayesian Inference
S Mandt, MD Hoffman, DM Blei
arXiv preprint arXiv:1704.04289, 2017
5232017
Underspecification presents challenges for credibility in modern machine learning
A D’Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...
arXiv preprint arXiv:2011.03395 1 (3), 2020
4382020
Tensorflow distributions
JV Dillon, I Langmore, D Tran, E Brevdo, S Vasudevan, D Moore, B Patton, ...
arXiv preprint arXiv:1711.10604, 2017
4322017
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
3232016
Deep Probabilistic Programming
D Tran, MD Hoffman, RA Saurous, E Brevdo, K Murphy, DM Blei
arXiv preprint arXiv:1701.03757, 2017
2232017
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
209*2014
Bayesian nonparametric matrix factorization for recorded music
M Hoffman, D Blei, P Cook
Proc. ICML, 439-446, 2010
2062010
Sparse stochastic inference for latent dirichlet allocation
D Mimno, M Hoffman, D Blei
arXiv preprint arXiv:1206.6425, 2012
1862012
What are Bayesian neural network posteriors really like?
P Izmailov, S Vikram, MD Hoffman, AGG Wilson
International conference on machine learning, 4629-4640, 2021
1732021
Nonparametric variational inference
S Gershman, M Hoffman, D Blei
arXiv preprint arXiv:1206.4665, 2012
1722012
Structured stochastic variational inference
MD Hoffman, DM Blei
Artificial Intelligence and Statistics, 2015
165*2015
A variational analysis of stochastic gradient algorithms
S Mandt, M Hoffman, D Blei
International Conference on Machine Learning, 354-363, 2016
1422016
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
1282016
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Články 1–20