The first article in this series will introduce perceptrons and the adaline (ADAptive LINear NEuron), which fall into the category of single-layer neural networks. The perceptron is not only the first algorithmically described learning algorithm [1], but it is also very intuitive, easy to impleme...
In context of pattern classification, such an algorithm could be useful to determine if a sample belongs to one class or the other.To put the perceptron algorithm into the broader context of machine learning: The perceptron belongs to the category of supervised learning algorithms, single-layer ...
CryoDRGN approximates the function V directly by using a multilayer perceptron (MLP)37. Instead of supplying the 3D coordinates into the MLP, cryoDRGN encodes the coordinates using a specific positional encoding12. The 2D projection at a specific angle is computed from positional encodings of the...
The most predictive cell type contexts for nominating therapeutic targets of IBD are CD4+αβ memory T cells, enterocytes of epithelium of large intestine, T follicular helper cells, plasmablasts and myeloid dendritic cells (Fig.5d). The intestinal barrier comprises a thick mucus layer with antimic...
▮▮▮▮ 3. chapter 3: 单图深度估计:点云生成的第一步 (Single Image Depth Estimation: The First Step in Point Cloud Generation) ▮▮▮▮▮▮▮ 3.1 深度估计的理论基础与经典算法 (Theoretical Basis and Classical Algorithms for Depth Estimation) ...
Single-cell transcriptomics (SCT) sequencing technology enables the simultaneous measurement of thousands of genes in cells [5,6,7]. In addition to gene expression, the data usually also contain additional characteristics such as cell type. Since different cell types have different gene expression pro...
The hyperparameters here are not only model-specific parameters but also the common neural network parameters that must be tuned, such as the number of neurons in the neural network layer, activation function selection, weight decay, and learning rate. Note that hyperparameter tuning is an ...
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In this work, we develop a computational celltyping method for scATAC-seq, named Cellcano. Cellcano implements a two-round supervised learning algorithm. It first trains a multi-layer perceptron (MLP) on the reference dataset and predicts cell types in target data. From the prediction results,...
We found that the trained classifiers yield comparable AUROC scores and we selected the multi-layer perceptron (MLP) as the optimal one, based on its superior performance on the training dataset in 5-fold cross validation (Additional file 1: Fig. S4A). We compared the performance of our train...