Python Transformer-networks Resources

PyTorch implementation of Continuous Augmented Positional Embeddings (CAPE), by Likhomanenko et al. Enhance your Transformer positional embeddings with easy-to-use augmentations!

Neural Fluid Fields This is a small library for doing fluid simulation with neural fields. Check out our review paper, Neural Fields in Visual Computi

Light Field Networks Project Page | Paper | Data | Pretrained Models Vincent Sitzmann*, Semon Rezchikov*, William Freeman, Joshua Tenenbaum, Frédo Dur

Are Transformers More Robust Than CNNs? Pytorch implementation for NeurIPS 2021 Paper: Are Transformers More Robust Than CNNs? Our implementation is b

Plenoxels: Radiance Fields without Neural Networks Alex Yu*, Sara Fridovich-Keil*, Matthew Tancik, Qinhong Chen, Benjamin Recht, Angjoo Kanazawa UC Be

SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer

A modular PyTorch library for optical flow estimation using neural networks

REGO-Deformable DETR By Zhe Chen, Jing Zhang, and Dacheng Tao. This repository is the implementation of the paper Recurrent Glimpse-based Decoder for

TransVTSpotter: End-to-end Video Text Spotter with Transformer Introduction A Multilingual, Open World Video Text Dataset and End-to-end Video Text Sp

Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"

Fourier Feature Networks and Neural Volume Rendering This repository is a companion to a lecture given at the University of Cambridge Engineering Depa

Plenoxels: Radiance Fields without Neural Networks Alex Yu*, Sara Fridovich-Keil*, Matthew Tancik, Qinhong Chen, Benjamin Recht, Angjoo Kanazawa UC Be

DiffMG This repository contains the code for our KDD 2021 Research Track paper: DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neura

Introduction K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce. Installation PyTor

Trapper (Transformers wRAPPER) Trapper is an NLP library that aims to make it easier to train transformer based models on downstream tasks. It wraps h

Deep-Learning-Models-for-Network-Annomaly-Detection The modular app consists for mainly three annomaly detection algorithms. The system supports model

SimMIM By Zhenda Xie*, Zheng Zhang*, Yue Cao*, Yutong Lin, Jianmin Bao, Zhuliang Yao, Qi Dai and Han Hu*. This repo is the official implementation of

END TO END ASR TRANSFORMER 本项目基于transformer 6*encoder+6*decoder的基本结构构造的端到端的语音识别系统 Model Instructions 1.数据准备: 自行下载数据，遵循文件结构如下： ├── data │ ├── train │

LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and

CRGNN Paper ： Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090

MINERVA Meandering In Networks of Entities to Reach Verisimilar Answers Code and models for the paper Go for a Walk and Arrive at the Answer - Reasoni

FDRL-PC-Dyspan Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks. This repository contains the entire code

yandex-shifts-weather The repository contains information about my solution for the Weather Prediction track in the Yandex Shifts challenge https://re

This is code of RID-Noise. Reproduce RID-Noise Results Toy tasks Please refer to the notebook ridnoise.ipynb to view experiments on three toy tasks. B

CCasGNN A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics,

RaceBERT -- A transformer based model to predict race and ethnicty from names Installation pip install racebert Using a virtual environment is highly

Flexible Networks for Learning Physical Dynamics of Deformable Objects (2021) By Jinhyung Park, Dohae Lee, In-Kwon Lee from Yonsei University (Seoul,

SalFBNet This repository includes Pytorch implementation for the following paper: SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolu

CRGNN Paper ： Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090

Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks Work accepted at NeurIPS'21 [paper, video]. If you use this code in

Transformer-in-Transformer An Implementation of the Transformer in Transformer paper by Han et al. for image classification, attention inside local pa

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Papers about explainability of GNNs

:speaker: Deep Learning & 3D Convolutional Neural Networks for Speaker Verification

Unsupervised Image to Image Translation with Generative Adversarial Networks Paper: Unsupervised Image to Image Translation with Generative Adversaria

DAGAN This is the official implementation code for DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruct

Dynamic Capacity Networks using Tensorflow Dynamic Capacity Networks (DCN; http://arxiv.org/abs/1511.07838) implementation using Tensorflow. DCN reduc

Hierarchical Attention Networks for Document Classification This is an implementation of the paper Hierarchical Attention Networks for Document Classi

MemN2N Implementation of End-To-End Memory Networks with sklearn-like interface using Tensorflow. Tasks are from the bAbl dataset. Get Started git clo

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

tf_cnnvis A blog post describing the library: https://medium.com/@falaktheoptimist/want-to-look-inside-your-cnn-we-have-just-the-right-tool-for-you-ad

TensorFlow implementation of 3D Convolutional Neural Networks for Speaker Verification - Official Project Page - Pytorch Implementation This repositor

MOVED TO HERE Spatial Transformer Networks Spatial Transformer Networks (STN) is a dynamic mechanism that produces transformations of input images (or

Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks - Official Project Page This repository contains the code develope

Attend, Infer, Repeat: Fast Scene Understanding with Generative Models This is an unofficial Tensorflow implementation of Attend, Infear, Repeat (AIR)

Semi-Supervised Learning with Ladder Networks in Keras This is an implementation of Ladder Network in Keras. Ladder network is a model for semi-superv

**This project is no longer active. Please check out TensorFlow.js.** The Keras.js demos still work but is no longer updated. Run Keras models in the

Training Structured Neural Networks Through Manifold Identification and Variance Reduction This repository is a pytorch implementation of the Regulari

PFD：Pose-guided Feature Disentangling for Occluded Person Re-identification based on Transformer This repo is the official implementation of "Pose-gui

Learning Tracking Representations via Dual-Branch Fully Transformer Networks DualTFR ⭐ We achieves the runner-ups for both VOT2021ST (short-term) and

TransZero [arXiv] This repository contains the testing code for the paper "TransZero: Attribute-guided Transformer for Zero-Shot Learning" accepted to

Vision Transformer(ViT) in Tensorflow2 Tensorflow2 implementation of the Vision Transformer(ViT). This repository is for An image is worth 16x16 words

Graph Posterior Network This is the official code repository to the paper Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classifica

Alternatives to Deep Neural Networks for Function Approximations in Finance Code companion repo Overview This is a repository of Python code to go wit

SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal This is the official pytorch code for SSAT: A Symmetric Semantic-

Convert ONNX model graph to Keras model format.

Object Detection with YOLOv3 Bu projede YOLOv3-608 modeli kullanılmıştır. Requirements Python 3.8 OpenCV Numpy Documentation Yolo ile ilgili detaylı b

CAPGNN Source code and dataset of the paper "Contrastive Adaptive Propagation Graph Neural Networks forEfficient Graph Learning" Paper URL: https://ar

Official-PyTorch-Implementation-of-TransMEF Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fu

UPT: Unary–Pairwise Transformers This repository contains the official PyTorch implementation for the paper Frederic Z. Zhang, Dylan Campbell and Step

TC-GNN (Running Sparse GNN on Dense Tensor Core on Ampere GPU) Cite this project and paper. @inproceedings{TC-GNN, title={TC-GNN: Accelerating Spars

Efficient Two-Step Networks for Temporal Action Segmentation This repository provides a PyTorch implementation of the paper Efficient Two-Step Network

NLP-Pytorch-Assignment An assignment from my grad-level data mining course (before I started personal projects) demonstrating some experience with NLP

With Py-Autocrack you can crack WPA2 networks in no time. All based on Aircrack-ng and Crunch.

Generative Modeling by Estimating Gradients of the Data Distribution This repo contains the official implementation for the NeurIPS 2019 paper Generat

This repository contains the similarity metrics designed and evaluated in the paper, and instructions and code to re-run the experiments. Implementation in the deep-learning framework PyTorch

MoViNet-pytorch Pytorch unofficial implementation of MoViNets: Mobile Video Networks for Efficient Video Recognition. Authors: Dan Kondratyuk, Liangzh

This is the project page for the paper: Architecture Disentanglement for Deep Neural Networks, Jie Hu, Liujuan Cao, Tong Tong, Ye Qixiang, ShengChuan

Reminder ST-GCN has transferred to MMSkeleton, and keep on developing as an flexible open source toolbox for skeleton-based human understanding. You a

Introduction New: Interactive demo using Google Colaboratory can be found here TTS-Cube is an end-2-end speech synthesis system that provides a full p

Pose Residual Network This repository contains a PyTorch implementation of the Pose Residual Network (PRN) presented in our ECCV 2018 paper: Muhammed

Structural Guidance for Transformer Language Models This repository accompanies the paper, Structural Guidance for Transformer Language Models, publis

HyperSPN This repository contains code for the paper: HyperSPNs: Compact and Expressive Probabilistic Circuits "HyperSPNs: Compact and Expressive Prob

SwinTrack This is the official repo for SwinTrack. A Simple and Strong Baseline Prerequisites Environment conda (recommended) conda create -y -n SwinT

Mask2Former: Masked-attention Mask Transformer for Universal Image Segmentation Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexander Kirillov, Ro

Interchange Intervention Training (IIT) Codebase for Inducing Causal Structure for Interpretable Neural Networks Release Notes 12/01/2021: Code and Pa

This repository is an official PyTorch(Geometric) implementation of G^2GNN in "Imbalanced Graph Classification via Graph-of-Graph Neural Networks". Th

Score Transformer This is the official repository for "Score Transformer": Score Transformer: Generating Musical Scores from Note-level Representation

Palo Alto Networks PAN-OS SDK for Python The PAN-OS SDK for Python (pan-os-python) is a package to help interact with Palo Alto Networks devices (incl

VT-UNet This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmentaion results of VT-UNet. Environmen

Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks Contributions A novel pairwise feature LSP to extract structural

FCN-pytorch-easiest Trying to be the easiest FCN pytorch implementation and just in a get and use fashion Here I use a handbag semantic segmentation f

Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner

hey-daug A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six

Temporal Segment Networks (TSN) We have released MMAction, a full-fledged action understanding toolbox based on PyTorch. It includes implementation fo

Darknet Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. D

Reproduce ResNet-v2 using MXNet Requirements Install MXNet on a machine with CUDA GPU, and it's better also installed with cuDNN v5 Please fix the ran

Introduction This repository contains the code for the paper Sentence Bottleneck Autoencoders from Transformer Language Models by Ivan Montero, Nikola

BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network) BERTAC is a framework that combines a

structural-probes Codebase for testing whether hidden states of neural networks encode discrete structures. Based on the paper A Structural Probe for

Are Sixteen Heads Really Better than One? This repository contains code to reproduce the experiments in our paper Are Sixteen Heads Really Better than

The Story of Heads This is the official repo for the following papers: (ACL 2019) Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy

The Lottery Ticket Hypothesis for Pre-trained BERT Networks Code for this paper The Lottery Ticket Hypothesis for Pre-trained BERT Networks. [NeurIPS

Norm-based Analysis of Transformer Implementations for 2 papers introducing to analyze Transformers using vector norms: Kobayashi+'20 Attention is Not

Admin Understanding the Difficulty of Training Transformers Guided by our analyses, we propose Adaptive Model Initialization (Admin), which successful

Length-Adaptive Transformer This is the official Pytorch implementation of Length-Adaptive Transformer. For detailed information about the method, ple

Continuous Sparsification Implementation of Continuous Sparsification (CS), a method based on l_0 regularization to find sparse neural networks, propo

New Release We released Adversarial training for both LM pre-training/finetuning and f-divergence. Large-scale Adversarial training for LMs: ALUM code

The Stem Cell Hypothesis Codes for our paper The Stem Cell Hypothesis: Dilemma behind Multi-Task Learning with Transformer Encoders published to EMNLP

MoT - Molecular Transformer Large-scale Pretraining for Molecular Property Prediction Samsung AI Challenge for Scientific Discovery This repository is