Learn Generative AI with PyTorch (Manning Publications, 2024)

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

Pure C multi modal 3D Hybrid GAN using Cross attention, attention and convolution

The Enterprise-Grade Production-Ready Multi-Agent Orchestration Framework Join our Community: https://discord.com/servers/agora-999382051935506503

Tensorflow implementation of a 3D-CNN U-net with Grid Attention and DSV for pancreas segmentation trained on CT-82.

Contrastive-LSH Embedding and Tokenization Technique for Multivariate Time Series Classification

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

The purpose of this project is to understand how the Transformers work and to build a Vision Transformer

FlashAttention (Metal Port)

This study introduces RMFNet, a sophisticated attention-based model designed to enhance the efficacy of early-stage brain tumor detection through advanced feature extraction methodologies.

The attention heads in the Transformer architecture possess a variety of capabilities. This is a carefully compiled list that summarizes the diverse functions of the attention heads.

LSTM-ARIMA with Attention and multiplicative decomposition for sophisticated stock forecasting.

Implementation of 💍 Ring Attention, from Liu et al. at Berkeley AI, in Pytorch

Training-free Post-training Efficient Sub-quadratic Complexity Attention. Implemented with OpenAI Triton.

This is an unofficial Pytorch implementation of the Infini Attention mechanism introduced in the paper : "Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention". Note that the official code for the paper has not been released yet. In case of issues, add a PR (add an explanation of the changes made and why so?)

STAD-GCN: Spatial-Temporal Attention-based Dynamic Graph Convolutional Network for Retail Market Price Prediction, pytorch version (ESWA 2024)

A Decoder-only Transfomer model for text generation.

A simple but complete full-attention transformer with a set of promising experimental features from various papers

A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction

An attention based approach to convert Indian Sign Language to Text using simulated hand gesture data