emstoudenmire/TNML
Tensor network machine learning. Based on the paper "Supervised Learning with Quantum Inspired Tensor Networks" http://arxiv.org/abs/1605.05775
This project helps researchers and practitioners in quantum-inspired machine learning experiment with tensor network models. It takes image datasets, such as MNIST, as input to train and test Matrix Product State (MPS) models for classification. The primary users are those exploring novel machine learning architectures, particularly physicists or computer scientists with a background in tensor networks.
163 stars. No commits in the last 6 months.
Use this if you are a researcher interested in exploring the foundational concepts of supervised learning with quantum-inspired tensor networks, specifically using Matrix Product States for classification.
Not ideal if you need a high-performance, production-ready machine learning library for general image classification or if you require state-of-the-art training speeds for MPS models.
Stars
163
Forks
54
Language
C++
License
MIT
Category
Last pushed
Apr 09, 2019
Commits (30d)
0
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