| Stochastic gradient hamiltonian monte carlo T Chen, E Fox, C Guestrin International conference on machine learning, 1683-1691, 2014 | 480 | 2014 |
| 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 | 465* | 2011 |
| 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 | 318 | 2008 |
| A complete recipe for stochastic gradient MCMC YA Ma, T Chen, EB Fox arXiv preprint arXiv:1506.04696, 2015 | 288 | 2015 |
| 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 | 212 | 2011 |
| Nonparametric Bayesian learning of switching linear dynamical systems E Fox, E Sudderth, M Jordan, A Willsky Advances in Neural Information Processing Systems 21, 457-464, 2008 | 210 | 2008 |
| Sparse graphs using exchangeable random measures F Caron, EB Fox Journal of the Royal Statistical Society. Series B, Statistical Methodology …, 2017 | 162 | 2017 |
| 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 | 162 | 2009 |
| A bayesian approach for predicting the popularity of tweets T Zaman, EB Fox, ET Bradlow Annals of Applied Statistics 8 (3), 1583-1611, 2014 | 153 | 2014 |
| Bayesian nonparametric learning of complex dynamical phenomena EB Fox Massachusetts Institute of Technology, 2009 | 142 | 2009 |
| Nonparametric Bayesian learning of switching linear dynamical systems EB Fox, EB Sudderth, MI Jordan, AS Willsky Advances in Neural Information Processing Systems, 457-464, 2009 | 104 | 2009 |
| Joint modeling of multiple time series via the beta process with application to motion capture segmentation EB Fox, MC Hughes, EB Sudderth, MI Jordan Annals of Applied Statistics 8 (3), 1281-1313, 2014 | 93 | 2014 |
| 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 | 93 | 2010 |
| Learning the parameters of determinantal point process kernels RH Affandi, E Fox, R Adams, B Taskar International Conference on Machine Learning, 1224-1232, 2014 | 78 | 2014 |
| Expectation-maximization for learning determinantal point processes J Gillenwater, A Kulesza, E Fox, B Taskar arXiv preprint arXiv:1411.1088, 2014 | 76 | 2014 |
| Stochastic variational inference for hidden Markov models NJ Foti, J Xu, D Laird, EB Fox arXiv preprint arXiv:1411.1670, 2014 | 66 | 2014 |
| Stochastic variational inference for hidden Markov models NJ Foti, J Xu, D Laird, EB Fox arXiv preprint arXiv:1411.1670, 2014 | 66 | 2014 |
| Control variates for stochastic gradient MCMC J Baker, P Fearnhead, EB Fox, C Nemeth Statistics and Computing 29 (3), 599-615, 2019 | 61 | 2019 |
| Hierarchical Dirichlet processes for tracking maneuvering targets EB Fox, EB Sudderth, AS Willsky 2007 10th international conference on information fusion, 1-8, 2007 | 60 | 2007 |
| Approximate inference in continuous determinantal point processes RH Affandi, EB Fox, B Taskar arXiv preprint arXiv:1311.2971, 2013 | 51 | 2013 |
