| Optimal transport mapping via input convex neural networks A Makkuva, A Taghvaei, S Oh, J Lee International Conference on Machine Learning, 6672-6681, 2020 | 222 | 2020 |
| Variational Wasserstein gradient flow J Fan, Q Zhang, A Taghvaei, Y Chen arXiv preprint arXiv:2112.02424, 2021 | 66 | 2021 |
| Scalable computations of wasserstein barycenter via input convex neural networks J Fan, A Taghvaei, Y Chen arXiv preprint arXiv:2007.04462, 2020 | 58 | 2020 |
| Kalman filter and its modern extensions for the continuous-time nonlinear filtering problem A Taghvaei, J De Wiljes, PG Mehta, S Reich Journal of Dynamic Systems, Measurement, and Control 140 (3), 030904, 2018 | 58 | 2018 |
| 2-Wasserstein approximation via restricted convex potentials with application to improved training for GANs A Taghvaei, A Jalali arXiv preprint arXiv:1902.07197, 2019 | 40 | 2019 |
| Fractional SIR epidemiological models A Taghvaei, TT Georgiou, L Norton, A Tannenbaum Scientific reports 10 (1), 20882, 2020 | 36 | 2020 |
| Feedback particle filter on riemannian manifolds and matrix lie groups C Zhang, A Taghvaei, PG Mehta IEEE Transactions on Automatic Control 63 (8), 2465-2480, 2017 | 36 | 2017 |
| An optimal transport formulation of the linear feedback particle filter A Taghvaei, PG Mehta 2016 American Control Conference (ACC), 3614-3619, 2016 | 36 | 2016 |
| Diffusion map-based algorithm for gain function approximation in the feedback particle filter A Taghvaei, PG Mehta, SP Meyn SIAM/ASA Journal on Uncertainty Quantification 8 (3), 1090-1117, 2020 | 35 | 2020 |
| An optimal transport formulation of the ensemble Kalman filter A Taghvaei, PG Mehta IEEE Transactions on Automatic Control 66 (7), 3052-3067, 2020 | 32 | 2020 |
| Accelerated flow for probability distributions A Taghvaei, P Mehta International conference on machine learning, 6076-6085, 2019 | 32 | 2019 |
| Gain function approximation in the feedback particle filter A Taghvaei, PG Mehta 2016 IEEE 55th Conference on Decision and Control (CDC), 5446-5452, 2016 | 32 | 2016 |
| Maximal power output of a stochastic thermodynamic engine R Fu, A Taghvaei, Y Chen, TT Georgiou Automatica 123, 109366, 2021 | 30 | 2021 |
| Energy harvesting from anisotropic fluctuations O Movilla Miangolarra, A Taghvaei, R Fu, Y Chen, TT Georgiou Physical Review E 104 (4), 044101, 2021 | 27 | 2021 |
| A survey of feedback particle filter and related controlled interacting particle systems (CIPS) A Taghvaei, PG Mehta Annual Reviews in Control 55, 356-378, 2023 | 25 | 2023 |
| An optimal transport formulation of Bayes’ law for nonlinear filtering algorithms A Taghvaei, B Hosseini 2022 IEEE 61st Conference on Decision and Control (CDC), 6608-6613, 2022 | 22 | 2022 |
| Geometry of finite-time thermodynamic cycles with anisotropic thermal fluctuations OM Miangolarra, A Taghvaei, Y Chen, TT Georgiou IEEE Control Systems Letters 6, 3409-3414, 2022 | 21 | 2022 |
| Feedback particle filter on matrix Lie groups C Zhang, A Taghvaei, PG Mehta 2016 American Control Conference (ACC), 2723-2728, 2016 | 18 | 2016 |
| Optimal transportation methods in nonlinear filtering A Taghvaei, PG Mehta IEEE Control Systems Magazine 41 (4), 34-49, 2021 | 16 | 2021 |
| Attitude estimation with feedback particle filter C Zhang, A Taghvaei, PG Mehta 2016 IEEE 55th Conference on Decision and Control (CDC), 5440-5445, 2016 | 16 | 2016 |
Prashant MehtaProfessor of Mechanical Science and Engineering, University of Illinoisillinois.edu의 이메일 확인됨