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cs.IT2025
Sample Abundance for Signal Processing: A Brief Introduction
Arian Eamaz, Farhang Yeganegi, Mojtaba Soltanalian
This paper reports, by way of introduction, on the advances made by our group and the broader signal processing community on the concept of sample abundance; a phenomenon that natu…
cs.LG2025
Physics-Inspired Binary Neural Networks: Interpretable Compression with Theoretical Guarantees
Arian Eamaz, Farhang Yeganegi, Mojtaba Soltanalian
Why rely on dense neural networks and then blindly sparsify them when prior knowledge about the problem structure is already available? Many inverse problems admit algorithm-unroll…