而高斯过程,它是随机变量的一个集合,任何有限个随机变量都有一个联合的高斯分布,它的表达式是f~GP(µ(x),K(x,x')),这里的µ(x)是均值函数(mean function),K(x,x')是协方差函数(covariance function)也被称为核函数(kernel function),刻画了数据之间的关系。 也就是说一个高斯过程,它是由均值函数和...
我们将看到,在相同的条件下,训练期间 ANN 的行为是由相关核来描述的,我们将其称为神经正切网络(neural tangent network)。 1.1 贡献 我们对 ANN 的网络函数 f_\theta 进行了研究,其将输入向量映射到输出向量,其中 \theta 表示ANN 的参数向量。在隐藏层宽度趋于无穷大的条件下,初始化时的网络函数 f_\theta ...
3.1.4 Radial basis function neural network Radial basis function neural network (RBFNN) is also a kind of non-linear multilayer feedforward neural network that based on function approximation theory. Based on the principle of Cover's theorem, RBFNN can find the best-fitting plane in high-dimensi...
The radial basis function network uses n local receptive fields to perform network mapping between inputs and outputs: (11.9)Rix=Ri|x−ci|/σi2 The receptive field function is typically a Gaussian function with maximum response at the center of the receptive field of width σ: (11.10)Rix=...
We propose herein a neural network based on curved kernels constituing an anisotropic family of functions and a learning rule to automatically tune the number of needed kernels to the frequency of the data in the input space. The model has been tested on
reducing the number of parameters in the input. Similar to the convolutional layer, the pooling operation sweeps a filter across the entire input, but the difference is that this filter does not have any weights. Instead, the kernel applies an aggregation function to the values within the recept...
We formulate each of these tasks as a kernel regression problem by considering a vector target function which takes in digits and outputs one-hot labels. Our kernel regression theory can be applied separately to each element of the target function vector (Methods), and a generalization error can...
Non-Local是王小龙在CVPR2018年提出的一个自注意力模型。Non-Local Neural Network和Non-Local Means非局部均值去噪滤波有点相似。普通的滤波都是3×3的卷积核,然后在整个图片上进行移动,处理的是3×3局部的信息。Non-Local Means操作则是结合了一个比较大的搜索...
毕竟最强大的 GNN 永远不会将两个不同的邻域特征映射到同一个嵌入,即聚合函数必须是单射 injective 的。因此,我们将 GNN 的聚合函数抽象为一种可以由 neural network 表示的 multiset function,并分析该函数是否能够表示为 injective multiset function。
You can use the network created usingunetfunction for GPU code generation after training withtrainnet(Deep Learning Toolbox). For details and examples, seeGenerate Code and Deploy Deep Neural Networks(Deep Learning Toolbox). References [1] Ronneberger, O., P. Fischer, and T. Brox. "U-Net...