[VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.

PyTorch implementation of some attentions for Deep Learning Researchers.

"Attention, Learn to Solve Routing Problems!"[Kool+, 2019], Capacitated Vehicle Routing Problem solver

This repository contain various types of attention mechanism like Bahdanau , Soft attention , Additive Attention , Hierarchical Attention etc in Pytorch, Tensorflow, Keras

Multi^2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT (Findings of ACL: EMNLP 2020)

Self-Supervised Vision Transformers for multiplexed imaging datasets

several types of attention modules written in PyTorch for learning purposes

Attention-based Induction Networks for Few-Shot Text Classification

This is the official repository of the original Point Transformer architecture.

The original transformer implementation from scratch. It contains informative comments on each block

EMNLP 2018: Multi-Head Attention with Disagreement Regularization; NAACL 2019: Information Aggregation for Multi-Head Attention with Routing-by-Agreement

2019达观杯信息提取第5名代码

Sentence encoder and training code for Mean-Max AAE

完整的原版transformer程序，complete origin transformer program

Image Captioning with Encoder as Efficientnet and Decoder as Decoder of Transformer combined with the attention mechanism.

Code for the runners up entry on the English subtask on the Shared-Task-On-Fighting the COVID-19 Infodemic, NLP4IF workshop, NAACL'21.

The Transformer model implemented from scratch using PyTorch. The model uses weight sharing between the embedding layers and the pre-softmax linear layer. Training on the Multi30k machine translation task is shown.

This project aims to implement the Scaled-Dot-Product Attention layer and the Multi-Head Attention layer using various Positional Encoding methods.

Pytorch Implementation of Transformers

Code and Datasets for the paper "A deep learning framework for high-throughput mechanism-driven phenotype compound screening and its application to COVID-19 drug repurposing", published on Nature Machine Intelligence in 2021.