TensorNetwork: A Library for Physics and Machine Learning
TensorNetwork is an open source library for implementing tensor network algorithms. Tensor networks are sparse data structures originally designed for simulating quantum many-body physics, but are currently also applied in a number of other research areas, including machine learning. We demonstrate the use of the API with applications both physics and machine learning, with details appearing in companion papers.
Code (2)
Tasks
BIG-bench Machine LearningTensor NetworksSimilar Papers 제목 키워드 기반
TensorNetwork for Machine Learning
We demonstrate the use of tensor networks for image classification with the TensorNetwork open source library. We explain in detail the encoding of image data into a matrix product state form, and describe how to contrac…
BIG-bench Machine LearningCPUGeneral ClassificationGPU+3TensorNetwork on TensorFlow: A Spin Chain Application Using Tree Tensor Networks
TensorNetwork is an open source library for implementing tensor network algorithms in TensorFlow. We describe a tree tensor network (TTN) algorithm for approximating the ground state of either a periodic quantum spin cha…
GPUTensor NetworksFrom Physics-Based Models to Predictive Digital Twins via Interpretable Machine Learning
This work develops a methodology for creating a data-driven digital twin from a library of physics-based models representing various asset states. The digital twin is updated using interpretable machine learning. Specifi…
BIG-bench Machine LearningInterpretable Machine LearningXLB: A differentiable massively parallel lattice Boltzmann library in Python
The lattice Boltzmann method (LBM) has emerged as a prominent technique for solving fluid dynamics problems due to its algorithmic potential for computational scalability. We introduce XLB library, a Python-based differe…
CPUGPUBayesian Inference in Physics-Based Nonlinear Flame Models
This study uses a Bayesian machine learning method to infer the parameters of a physics-based model of a bluff-body-stabilised flame in real-time. An ensemble of neural networks is trained on a library of simulated flame…
Bayesian Inference