Search Results for author: Ishan Deshpande

Found 4 papers, 1 papers with code

Fast exploration and learning of latent graphs with aliased observations

no code implementations13 Mar 2023 Miguel Lazaro-Gredilla, Ishan Deshpande, Sivaramakrishnan Swaminathan, Meet Dave, Dileep George

We consider the problem of recovering a latent graph where the observations at each node are \emph{aliased}, and transitions are stochastic.

Efficient Exploration

Max-Sliced Wasserstein Distance and its use for GANs

no code implementations CVPR 2019 Ishan Deshpande, Yuan-Ting Hu, Ruoyu Sun, Ayis Pyrros, Nasir Siddiqui, Sanmi Koyejo, Zhizhen Zhao, David Forsyth, Alexander Schwing

Generative adversarial nets (GANs) and variational auto-encoders have significantly improved our distribution modeling capabilities, showing promise for dataset augmentation, image-to-image translation and feature learning.

Image-to-Image Translation Translation

Generative Modeling using the Sliced Wasserstein Distance

1 code implementation CVPR 2018 Ishan Deshpande, Ziyu Zhang, Alexander Schwing

While this is particularly true for early GAN formulations, there has been significant empirically motivated and theoretically founded progress to improve stability, for instance, by using the Wasserstein distance rather than the Jenson-Shannon divergence.

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