( en | de | ru )

 

Disambiguation of "Ravichandar, Harish Chaandar"

Author of the publication

copydeleteadd this publication to your clipboard
Bayesian human intention inference through multiple model filtering with gaze-based priors.

, , and . FUSION, page 2296-2302. IEEE, (2016)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Ramya Ravichandar

Harish Balasubramaniam

Harish Kommera

Harish Nagarajan

Harish Parala

 

Other publications of authors with the same name

Learning Stable Nonlinear Dynamical Systems with External Inputs using Gaussian Mixture Models., , , , and . ACC, page 4825-4830. IEEE, (2018)Human intention inference and motion modeling using approximate E-M with online learning., and . IROS, page 1819-1824. IEEE, (2015)Learning Partially Contracting Dynamical Systems from Demonstrations., , and . CoRL, volume 78 of Proceedings of Machine Learning Research, page 369-378. PMLR, (2017)Bayesian human intention inference through multiple model filtering with gaze-based priors., , and . FUSION, page 2296-2302. IEEE, (2016)Learning and Predicting Sequential Tasks Using Recurrent Neural Networks and Multiple Model Filtering., , , and . AAAI Fall Symposia, AAAI Press, (2016)Learning and synchronization of movement primitives for bimanual manipulation tasks., , and . CDC, page 945-950. IEEE, (2016)Learning position and orientation dynamics from demonstrations via contraction analysis., and . Auton. Robots, 43 (4): 897-912 (2019)Gyro-aided image-based tracking using mutual information optimization and user inputs., and . SMC, page 858-863. IEEE, (2014)Human intention inference through interacting multiple model filtering., and . MFI, page 220-225. IEEE, (2015)Learning periodic motions from human demonstrations using transverse contraction analysis., , and . ACC, page 4853-4858. IEEE, (2016)