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This is a sample code of "LSTM encoder-decoder with attention mechanism" mainly for understanding a recently developed machine translation framework based on deep neural networks.

Sample iOS app for a blog post about gesture recognition and attention to detail

This is a PyTorch implementation of the paper: "Processing Megapixel Images with Deep Attention-Sampling Models".

PyTorch implementation of "Effective Approaches to Attention-based Neural Machine Translation" using scheduled sampling to improve the parameter estimation process.

Source code of the paper Multi-Granularity Part Sampling Attention for Fine-Grained Visual Classification

Boltzmann Attention Sampling for Image Analysis with Small Objects

GINOT is a deep learning model that combines transformers with neural operators for accurate forward predictions on arbitrary 2D and 3D geometries. It processes surface point clouds using attention-based encoding with sampling and grouping, ensuring robustness to point density, order invariance, ... Read more

This repository contains codes and sample data from the journal paper "Rapid Mapping of landslide on SAR data by Attention U-net" by Nava et al (2022). With this repository files you can train the Attention U-Net segmentation model on Sentinel-1 SAR amplitude landslide data sampled for the Hokkai... Read more

The PyTorch implementation for multi-task attention guided network (MTAGN) in End to End Multi-task learning with Attention for Multi-objective Fault Diagnosis under Small Sample

Attention-based sampler in TASN (Trilinear Attention Sampling Network)