6 citations · 13 across the 8 of their papers we have counts for
8 papers
Distilling the Undistillable: Learning from a Nasty Teacher
Surgan Jandial, Yash Khasbage, Arghya Pal +2
The inadvertent stealing of private/sensitive information using Knowledge Distillation (KD) has been getting significant attention recently and has guided subsequent defense effort…
A Deep Learning Approach Using Masked Image Modeling for Reconstruction of Undersampled K-spaces
Kyler Larsen, Arghya Pal, Yogesh Rathi
Magnetic Resonance Imaging (MRI) scans are time consuming and precarious, since the patients remain still in a confined space for extended periods of time. To reduce scanning time,…
A review and experimental evaluation of deep learning methods for MRI reconstruction
Arghya Pal, Yogesh Rathi
Following the success of deep learning in a wide range of applications, neural network-based machine-learning techniques have received significant interest for accelerating magneti…
Synthesize-It-Classifier: Learning a Generative Classifier through RecurrentSelf-analysis
Arghya Pal, Rapha Phan, KokSheik Wong
In this work, we show the generative capability of an image classifier network by synthesizing high-resolution, photo-realistic, and diverse images at scale. The overall methodolog…
Generative Adversarial Data Programming
Arghya Pal, Vineeth N Balasubramanian
The paucity of large curated hand-labeled training data forms a major bottleneck in the deployment of machine learning models in computer vision and other fields. Recent work (Data…
Zero-Shot Task Transfer
Arghya Pal, Vineeth N Balasubramanian
In this work, we present a novel meta-learning algorithm, i.e. TTNet, that regresses model parameters for novel tasks for which no ground truth is available (zero-shot tasks). In o…
C4Synth: Cross-Caption Cycle-Consistent Text-to-Image Synthesis
K J Joseph, Arghya Pal, Sailaja Rajanala +1
Generating an image from its description is a challenging task worth solving because of its numerous practical applications ranging from image editing to virtual reality. All exist…
Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data
Arghya Pal, Vineeth N Balasubramanian
Paucity of large curated hand-labeled training data for every domain-of-interest forms a major bottleneck in the deployment of machine learning models in computer vision and other…