62 citations · 177 across the 45 of their papers we have counts for
6 papers · 1 filter
MR-GAN: Manifold Regularized Generative Adversarial Networks
Qunwei Li, Bhavya Kailkhura, Rushil Anirudh +3
Despite the growing interest in generative adversarial networks (GANs), training GANs remains a challenging problem, both from a theoretical and a practical standpoint. To address…
MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense
Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura +1
Solving inverse problems continues to be a central challenge in computer vision. Existing techniques either explicitly construct an inverse mapping using prior knowledge about the…
Multiple Subspace Alignment Improves Domain Adaptation
Kowshik Thopalli, Rushil Anirudh, Jayaraman J. Thiagarajan +1
We present a novel unsupervised domain adaptation (DA) method for cross-domain visual recognition. Though subspace methods have found success in DA, their performance is often limi…
Understanding Deep Neural Networks through Input Uncertainties
Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh +1
Techniques for understanding the functioning of complex machine learning models are becoming increasingly popular, not only to improve the validation process, but also to extract n…
Unsupervised Dimension Selection using a Blue Noise Spectrum
Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar +1
Unsupervised dimension selection is an important problem that seeks to reduce dimensionality of data, while preserving the most useful characteristics. While dimensionality reducti…
An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks
Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura +1
Solving inverse problems continues to be a challenge in a wide array of applications ranging from deblurring, image inpainting, source separation etc. Most existing techniques solv…