The article "Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing" by Vishal Monga, Yuelong Li, and Yonina C. Eldar reviews the emerging technique of algorithm unrolling, which aims to address the black-box nature and large training set requirements of deep neural networks in signal and image processing. Algorithm unrolling connects iterative algorithms used in signal processing to deep neural networks, providing a more interpretable and efficient approach. The authors cover popular techniques for algorithm unrolling in various domains, including imaging, vision, and recognition, and discuss recent theoretical results. They also highlight the potential of unrolled networks in developing efficient, high-performance, and interpretable architectures from reasonable-sized training sets. The article concludes with a discussion on current limitations and suggests future research directions. Key applications of algorithm unrolling include single image super-resolution, blind image deblurring, and medical imaging, where the technique has shown significant performance improvements and computational efficiency.The article "Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing" by Vishal Monga, Yuelong Li, and Yonina C. Eldar reviews the emerging technique of algorithm unrolling, which aims to address the black-box nature and large training set requirements of deep neural networks in signal and image processing. Algorithm unrolling connects iterative algorithms used in signal processing to deep neural networks, providing a more interpretable and efficient approach. The authors cover popular techniques for algorithm unrolling in various domains, including imaging, vision, and recognition, and discuss recent theoretical results. They also highlight the potential of unrolled networks in developing efficient, high-performance, and interpretable architectures from reasonable-sized training sets. The article concludes with a discussion on current limitations and suggests future research directions. Key applications of algorithm unrolling include single image super-resolution, blind image deblurring, and medical imaging, where the technique has shown significant performance improvements and computational efficiency.