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Emily B. Fox
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Cited by
Year
Stochastic gradient hamiltonian monte carlo
T Chen, E Fox, C Guestrin
International conference on machine learning, 1683-1691, 2014
6462014
A sticky HDP-HMM with application to speaker diarization
EB Fox, EB Sudderth, MI Jordan, AS Willsky
The Annals of Applied Statistics, 1020-1056, 2011
510*2011
A complete recipe for stochastic gradient MCMC
YA Ma, T Chen, E Fox
Advances in neural information processing systems 28, 2015
3762015
An HDP-HMM for systems with state persistence
EB Fox, EB Sudderth, MI Jordan, AS Willsky
Proceedings of the 25th international conference on Machine learning, 312-319, 2008
3342008
Bayesian nonparametric inference of switching dynamic linear models
E Fox, EB Sudderth, MI Jordan, AS Willsky
IEEE Transactions on Signal Processing 59 (4), 1569-1585, 2011
2442011
Nonparametric Bayesian learning of switching linear dynamical systems
E Fox, E Sudderth, M Jordan, A Willsky
Advances in neural information processing systems 21, 2008
2412008
Sparse graphs using exchangeable random measures
F Caron, EB Fox
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2017
1982017
Curran Associates
H Wallach, H Larochelle, A Beygelzimer, F d’Alché-Buc, E Fox, R Garnett
Inc.: Red Hook, NY, USA 32, 8024-8035, 2019
1862019
A bayesian approach for predicting the popularity of tweets
T Zaman, EB Fox, ET Bradlow
The Annals of Applied Statistics 8 (3), 1583-1611, 2014
1762014
Sharing features among dynamical systems with beta processes
EB Fox, EB Sudderth, MI Jordan, AS Willsky
Advances in Neural Information Processing Systems, 549-557, 2009
1702009
Bayesian nonparametric learning of complex dynamical phenomena
EB Fox
Massachusetts Institute of Technology, 2009
1532009
Improving reproducibility in machine learning research: a report from the NeurIPS 2019 reproducibility program
J Pineau, P Vincent-Lamarre, K Sinha, V Larivière, A Beygelzimer, ...
Journal of Machine Learning Research 22, 2021
1062021
Joint modeling of multiple time series via the beta process with application to motion capture segmentation
EB Fox, MC Hughes, EB Sudderth, MI Jordan
The Annals of Applied Statistics 8 (3), 1281-1313, 2014
1032014
Bayesian nonparametric methods for learning Markov switching processes
EB Fox, EB Sudderth, MI Jordan, AS Willsky
IEEE Signal Processing Magazine 27 (6), 43-54, 2010
1032010
Learning the parameters of determinantal point process kernels
RH Affandi, E Fox, R Adams, B Taskar
International Conference on Machine Learning, 1224-1232, 2014
1012014
Neural granger causality
A Tank, I Covert, N Foti, A Shojaie, E Fox
arXiv preprint arXiv:1802.05842, 2018
962018
Stochastic variational inference for hidden Markov models
N Foti, J Xu, D Laird, E Fox
Advances in neural information processing systems 27, 2014
862014
Stochastic variational inference for hidden Markov models
N Foti, J Xu, D Laird, E Fox
Advances in neural information processing systems 27, 2014
862014
Expectation-maximization for learning determinantal point processes
JA Gillenwater, A Kulesza, E Fox, B Taskar
Advances in Neural Information Processing Systems 27, 2014
842014
Control variates for stochastic gradient MCMC
J Baker, P Fearnhead, EB Fox, C Nemeth
Statistics and Computing 29 (3), 599-615, 2019
782019
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Articles 1–20