Must-read papers on graph neural networks (GNN)

learning biology syllabus, geared for machine learning folks

Adaptive Graph Attention Auto-encoder for Spatial Domain Identification of Spatial Transcriptomics

Fast graph-regularized matrix factorization

MIT-18.06-线性代数-完整笔记

The implement of GNN based on Pytorch

Magnetic resonance imaging (MRI) images are known to be sparse. This is an implementation using non-convex penalty function that encourages sparsity.

定位综述 目前用于人脸定位的有两种主流方法，一种是基于级联形状回归模型，另一种就是基于深度学习的方法。级联形状回归方法就是使用回归模型，直接学习从人脸表征到人脸形状的映射函数，进而建立从表观到形状的对应关系。这种方法的学习依赖于训练集的选取，如果训练集中包含了复杂的姿态变化，学习到的函数测试性能就会比较好。现有很多基于回归的方法，其中比较突出的有颜水成的DCR（Deep Cascaded R…

use TCN and Transformer model for "Hourly Energy Consumption" data

Performed comparative analysis of BiLSTM, CNN-BiLSTM and CNN-BiLSTM with attention models for forecasting cases.