The machine cells are formed by an algorithm which is based on the maximum neural network. Another algorithm is used to find the part families associated with each machine cell. When compared with an existing algorithm, our algorithm shows better performance in terms of grouping efficiency and ...
We presentEP-DNN, a protocol for predicting enhancers based on chromatin features, in different cell types. Specifically, we use a deep neural network (DNN)-based architecture to extract enhancer signatures in a representative human embryonic stem cell type (H1) and a differentiated lung cell type...
NeuCA is a supervised cell label assignment method. It uses existing scRNA-seq data with known labels to train a neural network-based classifier and then predict cell labels in new data of interest. Figure1provides a schematic overview of the proposed method. Based on the training data, NeuCA...
深度学习框架Keras学习系列(二):神经网络与BP算法(Neural Network and BP Algorithm),程序员大本营,技术文章内容聚合第一站。
Focusing on the problems, we propose a leader-follower flocking algorithm based on a novel reinforcement learning (RL) model. We construct a homogeneous graph neural network (GNN) based multi-agent deep deterministic policy gradient (herein HGNN-MADDPG) algorithm model for multi-agent flocking ...
The network consists of simple processing elements that are interconnected via weights. The network is first trained using an appropriate learning algorithm for the estimation of interconnection weights. Once the network is trained, unknown test signals can be classified. The class of neural networks ...
does not generally lead to convergence of the derivatives of numerical solutions or the corresponding feedback control laws. in this work, we propose an efficient neural network-based policy iteration algorithm for solving ( 1.1 ). at the \((k+1)\) th iteration, \(k\ge 0\) , we shall...
神经网络中,这种从后往前的推导方法称为Backpropagation Algorithm,即我们常常听到的BP神经网络算法。它的算法流程如下所示: 上面采用的是SGD的方法,即每次迭代更新时只取一个点,这种做法一般不够稳定。所以通常会采用mini-batch的方法,即每次选取一些数据,例如,来进行训练,最后求平均值更新权重w。这种做法的实际效果会...
A neural network can also be used for association analysis. When you create a mining model using the Microsoft Neural Network algorithm, you can include multiple outputs, and the algorithm will create multiple networks. The number of networks contained in a single mining model contains depends on...
Shift Based AdaMax 同样也是为了加速二值网络的训练,改进了AdaMax优化器。具体算法如Algorithm3所示。 Shift Based AdaMax First Layer 虽然所有层的激活值和参数都是二值的,但第一层(输入层)的值是连续的,因为是原始图片。如果要整个网络都是二值化的,只需要对输入层做一个变换即可。一般使用8位的值来表示一个...