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P. Mehta

22 papers hereh-index 324k citations174 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author5
  • last author13

Across the 20 of 22 papers where every author was matched, so the position is known.

fields
  • math.OC10
  • math.PR7
  • eess.SY4
  • cs.LG1
same name
  • P. Mehta — 42 papers
  • P. Mehta — 20 papers, h 28
  • P. Mehta — 9 papers, h 19
  • P. Mehta — 6 papers, h 10
  • P. Mehta — 5 papers, h 15
  • P. Mehta — 3 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162025
most citedOptimal Rate of Convergence for Quasi-Stochastic Approximation

5 citations · 14 across the 11 of their papers we have counts for

collaborators
Showing eess.SYShow all

4 papers · 1 filter

eess.SY2021

Optimal Transportation Methods in Nonlinear Filtering: The feedback particle filter

Amirhossein Taghvaei, Prashant G. Mehta

Feedback particle filter (FPF) is a Monte-Carlo (MC) algorithm to approximate the solution of a stochastic filtering problem. In contrast to conventional particle filters, the Baye…

eess.SY2019

An Optimal Transport Formulation of the Ensemble Kalman Filter

Amirhossein Taghvaei, Prashant G. Mehta

Controlled interacting particle systems such as the ensemble Kalman filter (EnKF) and the feedback particle filter (FPF) are numerical algorithms to approximate the solution of the…

eess.SY2019

Bio-inspired Learning of Sensorimotor Control for Locomotion

Tixian Wang, Amirhossein Taghvaei, Prashant G. Mehta

This paper presents a bio-inspired central pattern generator (CPG)-type architecture for learning optimal maneuvering control of periodic locomotory gaits. The architecture is pres…

eess.SY2019★ 2 cited

Q-learning for POMDP: An application to learning locomotion gaits

Tixian Wang, Amirhossein Taghvaei, Prashant G. Mehta

This paper presents a Q-learning framework for learning optimal locomotion gaits in robotic systems modeled as coupled rigid bodies. Inspired by prevalence of periodic gaits in bio…

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