477 citations · 972 across the 72 of their papers we have counts for
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Gradient Inversion Attacks on Parameter-Efficient Fine-Tuning
Hasin Us Sami, Swapneel Sen, Amit K. Roy-Chowdhury +2
Federated learning (FL) allows multiple data-owners to collaboratively train machine learning models by exchanging local gradients, while keeping their private data on-device. To s…
Poisson2Sparse: Self-Supervised Poisson Denoising From a Single Image
Calvin-Khang Ta, Abhishek Aich, Akash Gupta +1
Image enhancement approaches often assume that the noise is signal independent, and approximate the degradation model as zero-mean additive Gaussian. However, this assumption does…
Ada-VSR: Adaptive Video Super-Resolution with Meta-Learning
Akash Gupta, Padmaja Jonnalagedda, Bir Bhanu +1
Most of the existing works in supervised spatio-temporal video super-resolution (STVSR) heavily rely on a large-scale external dataset consisting of paired low-resolution low-frame…
Deep Quantized Representation for Enhanced Reconstruction
Akash Gupta, Abhishek Aich, Kevin Rodriguez +2
While machine learning approaches have shown remarkable performance in biomedical image analysis, most of these methods rely on high-quality and accurate imaging data. However, col…
Non-Adversarial Video Synthesis with Learned Priors
Abhishek Aich, Akash Gupta, Rameswar Panda +3
Most of the existing works in video synthesis focus on generating videos using adversarial learning. Despite their success, these methods often require input reference frame or fai…