#Self-attention
Showing 26 of 26 repositories tagged #self-attention, ranked by stars
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!
Datasets, tools, and benchmarks for representation learning of code.
[CVPR 2025] Official PyTorch Implementation of MambaVision: A Hybrid Mamba-Transformer Vision Backbone
Recent Transformer-based CV and related works.
Implementation of various self-attention mechanisms focused on computer vision. Ongoing repository.
Pre-training of Deep Bidirectional Transformers for Language Understanding: pre-train TextCNN
[ICLR 2024] Official PyTorch implementation of FasterViT: Fast Vision Transformers with Hierarchical Attention
臺灣大學 (NTU) 李宏毅教授「機器學習 (Machine Learning) 2021 Spring 」課程筆記
The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-series imputation (impute multivariate incomplete time series containing NaN missing data/values with machine learning). https://arxiv.org/abs/2202.08516
A Structured Self-attentive Sentence Embedding
Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP
The official repo for [TPAMI'25] "HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model"
Live-bending a foundation model’s output at neural network level.
Awesome Transformers (self-attention) in Computer Vision
Variants of Vision Transformer and its downstream tasks
Neat (Neural Attention) Vision, is a visualization tool for the attention mechanisms of deep-learning models for Natural Language Processing (NLP) tasks. (framework-agnostic)
A Pytorch implementation of Global Self-Attention Network, a fully-attention backbone for vision tasks
ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks
Edge-Augmented Graph Transformer
A PyTorch implementation of Context Vector Data Description (CVDD), a method for Anomaly Detection on text.
An unofficial pytorch implementation of 'Efficient Infinite Context Transformers with Infini-attention'