Explores physics-informed imaging systems, including lensless imaging, deep learning for imaging challenges, and the development of noise models for low-light videos.
Covers the fundamental concepts of machine learning, including classification, algorithms, optimization, supervised learning, reinforcement learning, and various tasks like image recognition and text generation.
Introduces a functional framework for deep neural networks with adaptive piecewise-linear splines, focusing on biomedical image reconstruction and the challenges of deep splines.
