2 citations · 4 across the 4 of their papers we have counts for
8 papers
Neuromorphic Sampling of Sparse Signals
Abijith Jagannath Kamath, Chandra Sekhar Seelamantula
Neuromorphic sampling is a bioinspired and opportunistic analog-to-digital conversion technique, where the measurements are recorded only when there is a significant change in the…
Neuromorphic Sampling of Signals in Shift-Invariant Spaces
Abijith Jagannath Kamath, Chandra Sekhar Seelamantula
Neuromorphic sampling is a paradigm shift in analog-to-digital conversion where the acquisition strategy is opportunistic and measurements are recorded only when there is a signifi…
Data Interpolants -- That's What Discriminators in Higher-order Gradient-regularized GANs Are
Siddarth Asokan, Chandra Sekhar Seelamantula
We consider the problem of optimizing the discriminator in generative adversarial networks (GANs) subject to higher-order gradient regularization. We show analytically, via the lea…
Spider GAN: Leveraging Friendly Neighbors to Accelerate GAN Training
Siddarth Asokan, Chandra Sekhar Seelamantula
Training Generative adversarial networks (GANs) stably is a challenging task. The generator in GANs transform noise vectors, typically Gaussian distributed, into realistic data suc…
Risk Estimation Without Using Stein's Lemma -- Application to Image Denoising
Sagar Venkatesh Gubbi, Chandra Sekhar Seelamantula
We address the problem of image denoising in additive white noise without placing restrictive assumptions on its statistical distribution. In the recent literature, specific noise…
A Risk Minimization Framework for Channel Estimation in OFDM Systems
Karthik Upadhya, Chandra Sekhar Seelamantula, K. V. S. Hari
We address the problem of channel estimation for cyclic-prefix (CP) Orthogonal Frequency Division Multiplexing (OFDM) systems. We model the channel as a vector of unknown determini…