In this talk, I will give an overview of tensor network (TN) methods, which are efficient numerical approaches for the simulation of quantum many-body problems, and their application in machine learning (ML). In particular, I Will discuss how ideas inspired by quantum physics can be leveraged to do machine learning and improve deep learning methods. I will further showcase how tensor networks can be integrated with ML models for kernel learning and fully connected neural networks to do data classification and regression.
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https://www.skyroom.online/ch/schoolofnanoscience/weeklyseminars