Quantum Computing and Algorithms
This repo contains the code, notes, links, and other material from the reading group on:
Quantum Algorithms, Linear Algebra, Deep Learning, Machine Learning, and Natural Language Processing
Initial meetings started summer 2018 at Indiana University in Dr. Damir Cavar's lab. The goal of this reading and programming group is to promote the understanding of Quantum Algorithms and Computing, focusing on Machine Learning, and in particular for Natural Language Processing and Deep Learning.
We are reading:
- Richard J. Lipton and Kenneth W. Regan (2014) Quantum Algorithms via Linear Algebra: A Primer. MIT Press.
- Eleanor G. Rieffel and Wolfgang H. Polak (2014) Quantum Computing: A Gentle Introduction. MIT Press.
- Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016) The Deep Learning. MIT Press.
- Dan Jurafsky and James H. Martin (2008) Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Prentice Hall; 2nd edition. (3rd ed. draft)
- Philip N. Klein (2013) Coding the Matrix: Linear Algebra Through Computer Science Applications. Newtonian Press.
- The IBM Q Initiative and Quantum Information Software Kit (QISKit)
- The Microsoft Quantum Computing pages and the Microsoft Quantum Development Kit (Windows, macOS, Linux)
List of Quantum Computing simulators:
A colleague pointed out that there was a workshop in May 2018 in DC with very interesting publications and tutorials linked on their site: