Recorded 18 October 2023. Srinivasan Arunachalam of IBM Research, Almaden, presents "Overview of learning structured quantum states" at IPAM's Mathematical Aspects of Quantum Learning Workshop. Abstract: Learning an unknown n-qubit quantum state is a fundamental challenge in quantum computing theory and practice. Information-theoretically, it is well-known that tomography requires exponential in n many copies of an unknown state in order to estimate it upto small trace distance. But a natural question is, are there models of learning where fewer copies suffice and are there interesting classes of states that can be learned with fewer copies? In this talk, I will give a brief overview of learning Boolean functions, structured quantum states, and alternate learning models where efficient learning is possible. Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-ii-mathematical-aspects-of-quantum-learning/?tab=schedule