Publications

ArXiv preprints:

  1. A. Makkuva, A. Taghvaei, S. Oh, J. Lee, Optimal transport mapping via input-convex neural networks (arXiv)
  2. A. Taghvaei, P. G. Mehta, S. P. Meyn. Diffusion map-based algorithm for gain function approximation in the feedback particle filter (arXiv)
  3. A. Taghvaei, A. Jalali. 2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs, Feb, 2019 (arXiv)

Journal publications:

  1. 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)
  2. 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)
  3. 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:

  1. 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)
  2. A. Taghvaei, P. G. Mehta. Accelerated flow for probability distributions, International Conference on Machine Learning (ICML), Long Beach, June, 2019 (arXiv)
  3. 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)
  4. 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)
  5. 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)
  6. 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)
  7. 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)
  8. 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)
  9. C. Zhang, A. Taghvaei, P. G. Mehta. Attitude Estimation of a Wearable
    Motion Sensor, IEEE American Control Conference (ACC), Seattle, May, 2017 (link).
  10. 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)
  11. 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)
  12. 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)
  13. 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)
  14. 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)