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Piecewise-Polynomial Coupling Layers for Warp-Predicting Neural Networks

机译:翘曲预测神经网络的分段多项式耦合层

摘要

According to one implementation, a system includes a computing platform having a hardware processor and a system memory storing a software code including multiple artificial neural networks (ANNs). The hardware processor executes the software code to partition a multi-dimensional input vector into a first vector data and a second vector data, and to transform the second vector data using a first piecewise-polynomial transformation parameterized by one of the ANNs, based on the first vector data, to produce a transformed second vector data. The hardware processor further executes the software code to transform the first vector data using a second piecewise-polynomial transformation parameterized by another of the ANNs, based on the transformed second vector data, to produce a transformed first vector data, and to determine a multi-dimensional output vector based on an output from the plurality of ANNs.
机译:根据一个实现,一种系统包括计算平台,该计算平台具有硬件处理器和系统存储器,该系统存储器存储包括多个人工神经网络(ANN)的软件代码。硬件处理器执行软件代码,以将多维输入向量划分为第一向量数据和第二向量数据,并使用由其中一个人工神经网络参数化的第一分段多项式变换对第二向量数据进行变换,基于第一矢量数据,以产生变换后的第二矢量数据。硬件处理器还执行软件代码,以基于变换后的第二矢量数据,使用由另一个ANN设置参数的第二分段多项式变换来变换第一矢量数据,以生成变换后的第一矢量数据,并确定多基于来自多个ANN的输出的三维输出向量。

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