ArXiv preprints:
- A. Taghvaei, P. G. Mehta, An optimal transport formulation of the ensemble Kalman filter (arXiv)
- A. Makkuva, A. Taghvaei, S. Oh, J. Lee, Optimal transport mapping via input-convex neural networks (arXiv)
- A. Taghvaei, P. G. Mehta, S. P. Meyn. Diffusion map-based algorithm for gain function approximation in the feedback particle filter (arXiv)
- A. Taghvaei, A. Jalali. 2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs, Feb, 2019 (arXiv)
Journal publications:
- C. Zhang, A. Taghvaei, P. G. Mehta. A mean-field optimal control formulation for global optimization, IEEE Transactions on Automatic Control (TAC), May, 2018. (link) (pdf)
- A. Taghvaei, J de Wiljes, P. G. Mehta, and S. Reich. Kalman filter and its modern extensions for the continuous-time nonlinear filtering problem. ASME Journal of Dynamic Systems, Measurement, and Control, Nov, 2017 (link) (arXiv)
- C. Zhang, A. Taghvaei, P. G. Mehta. Feedback Particle Filter on Riemannian Manifolds and Matrix Lie groups, IEEE Transactions on Automatic Control (TAC), Nov, 2017. (link) (pdf)
Conference proceedings:
- T. Wang, A. Taghvaei. P. G. Mehta, Q-learning for POMDP: An application to learning locomotion gaits, IEEE Conference on Decision and Control (CDC), Dec, 2019 (arXiv)
- A. Taghvaei, P. G. Mehta. Accelerated flow for probability distributions, International Conference on Machine Learning (ICML), Long Beach, June, 2019 (arXiv)
- J. Kim, A. Taghvaei, P. G. Mehta, S. P. Meyn. An approach to duality in nonlinear filtering, IEEE American Control Conference (ACC), July, 2019 (arXiv)
- A. Taghvaei, P. G. Mehta, Error analysis of the stochastic linear feedback particle filter, IEEE Conference on Decision and Control (CDC), Miami Beach, December 2018 (link) (arXiv)
- J. Kim, A. Taghvaei, P. G. Mehta, Derivation and Extensions of the Linear Feedback Particle Filter based on Duality Formalisms, IEEE Conference on Decision and Control (CDC), Miami Beach, December 2018. (link) (arXiv)
- A. Taghvaei, P. G. Mehta, Error analysis of the linear feedback article filter, In Proc. of the 2018 American control conference (ACC), Milwaukee, June, 2018 (link) (arXiv)
- A. Taghvaei, J. W. Kim, P. G. Mehta, How regularization affects the critical points in linear neural networks, 31st Conference on Neural Information Processing Systems (NIPS), Long Beach, December, 2017 (link)
- A. Taghvaei, P. G. Mehta. S. P. Meyn, Error Estimates for the Kernel Gain Function Approximation in the Feedback Particle Filter, IEEE American Control Conference (ACC), Seattle, May 2017. (link) (arXiv)
- C. Zhang, A. Taghvaei, P. G. Mehta. Attitude Estimation of a Wearable
Motion Sensor, IEEE American Control Conference (ACC), Seattle, May, 2017 (link). - A. Taghvaei, P. G. Mehta, Gain Function Approximation in the Feedback Particle Filter, IEEE Conference on Decision and Control (CDC), Las Vegas, December 2016. (link) (arXiv)
- C. Zhang, A. Taghvaei, P. G. Mehta. Attitude Estimation with Feedback Particle Filter, IEE Conference on Decision and Control (CDC), Las Vegas, December, 2016. (link) (pdf)
- A. Taghvaei, P. G. Mehta. An Optimal Transport Formulation of Linear Feedback Particle Filter, In Proc. of the 2016 American Control Conference (ACC), Boston, June 2016. (link) (arXiv)
- C. Zhang, A. Taghvaei, P. G. Mehta. Feedback Particle Filter on Matrix Lie group, In Proc. of the 2016 American Control Conference (ACC), Boston, June, 2016. (link) (pdf)
- A. Taghvaei, S. A. Hutchinson, and P. G. Mehta. A Coupled Oscillator-based Control Architecture for Locomotory Gaits, IEEE Conference on Decision and Control (CDC), Los Angeles, December 2014. (link) (pdf)