Efficient Representations of Correlated Data as Tensor Networks

Math Physics Seminar
Monday, October 7, 2019 - 4:00pm for 1 hour (actually 50 minutes)
Skiles 005
Glen Evenbly – School of Physics, Georgia Tech – glen.evenbly@gmail.com
Federico Bonetto
Tensors networks are a formalism for expressing high-order tensors as networks of low-order tensors, thus can offer a compact representation of certain high-dimensional datasets. Originally developed in the context of quantum many-body theory, where they are used to efficiently represent quantum wave-functions, tensor networks have since found application in big data analytics, error correction, classical data compression and machine learning.
In this talk I will provide a brief introduction to the theory and application of tensor networks, and outline some of the current research directions in the tensor network program.