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Events

Computational and Applied Mathematics: Anuj Abhishek, Case Western Reserve University, Operator Learning for Inverse Problems

SAS 4201

Neural operators such as Deep Operator Networks (DeepONet) and Convolutional Neural Operators (CNO) have been shown to be fairly useful in approximating an operator between two function spaces. In this talk, we will briefly review two inverse problems that arise in Medical Imaging, namely EIT and QPAT. We will also describe the relevant operator learning architectures.…

Stochastics/Discrete Analysis Seminar: Lechao Xiao, Google DeepMind, Harmonic Analysis and Theory of Deep Learning

SAS 4201

The past decade has witnessed a remarkable surge in breakthroughs in artificial intelligence (AI), with the potential to profoundly impact various aspects of our lives. However, the fundamental mathematical principles underlying the success of deep learning, the core technology behind these breakthroughs, is still far from well-understood. In this presentation, I will share some interesting…