| Embarrassingly parallel inference for Gaussian processes MM Zhang, SA Williamson Journal of Machine Learning Research 20 (169), 1-26, 2019 | 27 | 2019 |
| Dispersal of Attaphila fungicola, a symbiotic cockroach of leaf-cutter ants ZI Phillips, MM Zhang, UG Mueller Insectes Sociaux 64, 277-284, 2017 | 20 | 2017 |
| Distributed, partially collapsed MCMC for Bayesian Nonparametrics A Dubey, MM Zhang, EP Xing, SA Williamson International Conference on Artificial Intelligence and Statistics 108, 3685 …, 2020 | 12 | 2020 |
| Sequential Gaussian processes for online learning of nonstationary functions MM Zhang, B Dumitrascu, SA Williamson, BE Engelhardt IEEE Transactions on Signal Processing 71, 1539-1550, 2023 | 11 | 2023 |
| Latent variable modeling with random features G Gundersen, M Zhang, B Engelhardt International Conference on Artificial Intelligence and Statistics, 1333-1341, 2021 | 11 | 2021 |
| Probabilistic time of arrival localization F Pérez-Cruz, PM Olmos, MM Zhang, H Huang IEEE Signal Processing Letters 26 (11), 1683-1687, 2019 | 11 | 2019 |
| Patient-specific effects of medication using latent force models with Gaussian processes LF Cheng, B Dumitrascu, M Zhang, C Chivers, M Draugelis, K Li, ... International Conference on Artificial Intelligence and Statistics, 4045-4055, 2020 | 7 | 2020 |
| Communication efficient parallel algorithms for optimization on manifolds B Saparbayeva, M Zhang, L Lin Advances in Neural Information Processing Systems 31, 2018 | 7 | 2018 |
| Accelerated algorithms for convex and non-convex optimization on manifolds L Lin, B Saparbayeva, MM Zhang, DB Dunson arXiv preprint arXiv:2010.08908, 2020 | 6 | 2020 |
| Robust and parallel Bayesian model selection MM Zhang, H Lam, L Lin Computational statistics & data analysis 127, 229-247, 2018 | 5 | 2018 |
| A new class of time dependent latent factor models with applications SA Williamson, MM Zhang, P Damien Journal of Machine Learning Research 21 (27), 1-24, 2020 | 4 | 2020 |
| Bayesian Non-linear Latent Variable Modeling via Random Fourier Features MM Zhang, GW Gundersen, BE Engelhardt arXiv preprint arXiv:2306.08352, 2023 | 2 | 2023 |
| Parallel markov chain monte carlo for the indian buffet process MM Zhang, A Dubey, SA Williamson arXiv preprint arXiv:1703.03457, 2017 | 2 | 2017 |
| Overcoming Posterior Collapse in Variational Autoencoders Via EM-Type Training Y Li, L Cheng, F Yin, MM Zhang, S Theodoridis ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 1 | 2023 |
| A semi-Bayesian nonparametric hypothesis test using maximum mean discrepancy with applications in generative adversarial networks F Fazeli-Asl, M Minyi Zhang, L Lin arXiv e-prints, arXiv: 2303.02637, 2023 | 1 | 2023 |
| Accelerated parallel non-conjugate sampling for Bayesian non-parametric models MM Zhang, SA Williamson, F Pérez-Cruz Statistics and Computing 32 (50), 1-25, 2022 | 1 | 2022 |
| Sparse Infinite Random Feature Latent Variable Modeling MM Zhang arXiv preprint arXiv:2205.09909, 2022 | 1 | 2022 |
| Online/Offline Learning to Enable Robust Beamforming: Limited Feedback Meets Deep Generative Models Y Li, Z Lin, K Li, MM Zhang arXiv preprint arXiv:2404.06055, 2024 | | 2024 |
| Preventing Model Collapse in Gaussian Process Latent Variable Models Y Li, Z Lin, F Yin, MM Zhang arXiv preprint arXiv:2404.01697, 2024 | | 2024 |
| Online Student- Processes with an Overall-local Scale Structure for Modelling Non-stationary Data T Sha, MM Zhang arXiv preprint arXiv:2311.00564, 2023 | | 2023 |
Sinead WilliamsonAssistant professor, University of Texas at AustinVerified email at mccombs.utexas.edu
