5 citations · 12 across the 8 of their papers we have counts for
10 papers
NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modeling
Shishira R Maiya, Sharath Girish, Max Ehrlich +6
Implicit Neural Representations (INR) have recently shown to be powerful tool for high-quality video compression. However, existing works are limiting as they do not explicitly exp…
The First Principles of Deep Learning and Compression
Max Ehrlich
The deep learning revolution incited by the 2012 Alexnet paper has been transformative for the field of computer vision. Many problems which were severely limited using classical s…
Leveraging Bitstream Metadata for Fast, Accurate, Generalized Compressed Video Quality Enhancement
Max Ehrlich, Jon Barker, Namitha Padmanabhan +4
Video compression is a central feature of the modern internet powering technologies from social media to video conferencing. While video compression continues to mature, for many c…
A Frequency Perspective of Adversarial Robustness
Shishira R Maiya, Max Ehrlich, Vatsal Agarwal +3
Adversarial examples pose a unique challenge for deep learning systems. Despite recent advances in both attacks and defenses, there is still a lack of clarity and consensus in the…
ReLaX: Retinal Layer Attribution for Guided Explanations of Automated Optical Coherence Tomography Classification
Evan Wen, Rebecca Sorenson, Max Ehrlich
30 million Optical Coherence Tomography (OCT) imaging tests are issued annually to diagnose various retinal diseases, but accurate diagnosis of OCT scans requires trained eye care…
Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer
Arthita Ghosh, Max Ehrlich, Larry Davis +1
Urban material recognition in remote sensing imagery is a highly relevant, yet extremely challenging problem due to the difficulty of obtaining human annotations, especially on low…