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The Tensor Basis Neural Network (TBNN) package provides an interface for building, training, and testing neural networks for systems that have known invariance properties. This package is intended as a useful reference and starting point for researchers hoping to develop data-driven constitutive models for systems with known invariance properties.

一个多体量子态可以写成一个高阶张量（左侧），这个高阶张量可以分解成多个低阶张量的缩并（右侧）。 可以看到独立变量个数为 Nd\chi^2 ，如果 \chi 和N无关（对于1D gapped系统的基态来说是正确的），那么整个数值复杂度就只是 O(N) 。 为了建立MPS和DMRG的直观联系，可以把每个张量看成上小节提到 ...

2020年8月6日 · This package implements the vanilla Tensor Basis Neural Network [1] as the TBNN class, and also the Tensor Basis Neural Network for Scalar Flux Modeling [2] as the TBNNS class. They are described in the following references: [1] Ling, Kurzawski, Templeton. "Reynolds averaged turbulence modelling using deep …

2023年7月28日 · Reynolds数标度的基于张量的神经网络（ReS-TBNN）架构用于建模偏差压强 Hessian。 图2. 比较速度梯度张量不变量的联合概率密度函数的模拟结果。

2023年2月22日 · TBNN: totally-binary neural network for image classification. Published: 22 February 2023; Volume 19, pages 117–122, (2023) Cite this article

2018年12月6日 · 近来在了解卷积神经网络（cnn），后来查到cnn是受语音信号处理中时延神经网络（tdnn）影响而发明的。本篇的大部分内容都来自关于tdnn原始文献【1】的理解和整理。普通神经网络识别音素 在讲tdnn之前先说说一般的神经网络的是怎样识别音素的吧。假设要识别三个辅音"b", "d", "g"，那么我们可以设计 ...

The high resolution data is used to train TBNN, then TBNN will give prediction results of Reynolds stress anisotropic tensor from the RANS result. The prediction of TBNN will be compared with high resolution numerical simulation and wind tunnel results to …

2024年3月18日 · Several Tensor Basis Neural Network (TBNN) frameworks aimed at enhancing turbulence RANS modeling have recently been proposed in the literature as data-driven constitutive models for systems with...

The Tensor Basis Neural Network (TBNN) package provides an interface for building, training, and testing neural networks for systems that have known invariance properties. This package is intended as a useful reference and starting point for researchers hoping to develop data-driven constitutive models for systems with known invariance properties.