21 citations · 34 across the 20 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
Optimal transport mapping via input convex neural networks
Ashok Vardhan Makkuva, Amirhossein Taghvaei, Sewoong Oh +1
In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn t…
2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs
Amirhossein Taghvaei, Amin Jalali
We provide a framework to approximate the 2-Wasserstein distance and the optimal transport map, amenable to efficient training as well as statistical and geometric analysis. With t…
Accelerated Flow for Probability Distributions
Amirhossein Taghvaei, Prashant G. Mehta
This paper presents a methodology and numerical algorithms for constructing accelerated gradient flows on the space of probability distributions. In particular, we extend the recen…