2006 Repositories
Python radio-transformer-networks Libraries
Transformer - Transformer in PyTorch
Transformer 完成进度 Embeddings and PositionalEncoding with example. MultiHeadAttent
Code for the paper: Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution
Fusformer Code for the paper: "Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution" Plateform Python 3.8.5 + Pytor
AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation
AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation AniGAN: Style-Guided Generative Adversarial Networks for U
TSIT: A Simple and Versatile Framework for Image-to-Image Translation
TSIT: A Simple and Versatile Framework for Image-to-Image Translation This repository provides the official PyTorch implementation for the following p
NICE-GAN — Official PyTorch Implementation Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation
NICE-GAN-pytorch - Official PyTorch implementation of NICE-GAN: Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation
Official PyTorch implementation of the paper: DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample
DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample (ICCV 2021 Oral) Project | Paper Official PyTorch implementation of the pape
GAN-STEM-Conv2MultiSlice - Exploring Generative Adversarial Networks for Image-to-Image Translation in STEM Simulation
GAN-STEM-Conv2MultiSlice GAN method to help covert lower resolution STEM images generated by convolution methods to higher resolution STEM images gene
CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation
CDGAN CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation CDGAN Implementation in PyTorch This is the imple
Net2net - Network-to-Network Translation with Conditional Invertible Neural Networks
Net2Net Code accompanying the NeurIPS 2020 oral paper Network-to-Network Translation with Conditional Invertible Neural Networks Robin Rombach*, Patri
Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
U-GAT-IT — Official PyTorch Implementation : Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Imag
Official PyTorch implementation of GDWCT (CVPR 2019, oral)
This repository provides the official code of GDWCT, and it is written in PyTorch. Paper Image-to-Image Translation via Group-wise Deep Whitening-and-
AsymmetricGAN - Dual Generator Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
AsymmetricGAN for Image-to-Image Translation AsymmetricGAN Framework for Multi-Domain Image-to-Image Translation AsymmetricGAN Framework for Hand Gest
[ACM MM 2019 Oral] Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation
Contents Cycle-In-Cycle GANs Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Acknowledgments Relat
AttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation
AttentionGAN-v2 for Unpaired Image-to-Image Translation AttentionGAN-v2 Framework The proposed generator learns both foreground and background attenti
Official pytorch implementation of paper Dual-Level Collaborative Transformer for Image Captioning (AAAI 2021).
Dual-Level Collaborative Transformer for Image Captioning This repository contains the reference code for the paper Dual-Level Collaborative Transform
Meshed-Memory Transformer for Image Captioning. CVPR 2020
M²: Meshed-Memory Transformer This repository contains the reference code for the paper Meshed-Memory Transformer for Image Captioning (CVPR 2020). Pl
Implementation of 'X-Linear Attention Networks for Image Captioning' [CVPR 2020]
Introduction This repository is for X-Linear Attention Networks for Image Captioning (CVPR 2020). The original paper can be found here. Please cite wi
PyTorch code for MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning
MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning PyTorch code for our ACL 2020 paper "MART: Memory-Augmented Recur
Implementation of the Object Relation Transformer for Image Captioning
Object Relation Transformer This is a PyTorch implementation of the Object Relation Transformer published in NeurIPS 2019. You can find the paper here
Fashion Entity Classification
Fashion-Entity-Classification - Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. Zalando intends Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.
Adversarial-autoencoders - Tensorflow implementation of Adversarial Autoencoders
Adversarial Autoencoders (AAE) Tensorflow implementation of Adversarial Autoencoders (ICLR 2016) Similar to variational autoencoder (VAE), AAE imposes
DCGAN-tensorflow - A tensorflow implementation of Deep Convolutional Generative Adversarial Networks
DCGAN in Tensorflow Tensorflow implementation of Deep Convolutional Generative Adversarial Networks which is a stabilize Generative Adversarial Networ
Convnet transfer - Code for paper How transferable are features in deep neural networks?
How transferable are features in deep neural networks? This repository contains source code necessary to reproduce the results presented in the follow
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition This is a Torch implementation of "Deep Residual Learning for Image Recognition",Kaiming He, Xiangyu Zhan
Deep Inside Convolutional Networks - This is a caffe implementation to visualize the learnt model
Deep Inside Convolutional Networks This is a caffe implementation to visualize the learnt model. Part of a class project at Georgia Tech Problem State
Deep-Learning-Image-Captioning - Implementing convolutional and recurrent neural networks in Keras to generate sentence descriptions of images
Deep Learning - Image Captioning with Convolutional and Recurrent Neural Nets ========================================================================
Pointer-generator - Code for the ACL 2017 paper Get To The Point: Summarization with Pointer-Generator Networks
Note: this code is no longer actively maintained. However, feel free to use the Issues section to discuss the code with other users. Some users have u
DeepSpeech - Easy-to-use Speech Toolkit including SOTA ASR pipeline, influential TTS with text frontend and End-to-End Speech Simultaneous Translation.
(简体中文|English) Quick Start | Documents | Models List PaddleSpeech is an open-source toolkit on PaddlePaddle platform for a variety of critical tasks i
Computer-Vision-Paper-Reviews - Computer Vision Paper Reviews with Key Summary along Papers & Codes
Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 50+ Papers across Computer Visio
SimpleDepthEstimation - An unified codebase for NN-based monocular depth estimation methods
SimpleDepthEstimation Introduction This is an unified codebase for NN-based monocular depth estimation methods, the framework is based on detectron2 (
A video scene detection algorithm is designed to detect a variety of different scenes within a video
Scene-Change-Detection - A video scene detection algorithm is designed to detect a variety of different scenes within a video. There is a very simple definition for a scene: It is a series of logically and chronologically related shots taken in a specific order to depict an over-arching concept or story.
LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating
LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating (Dataset) The dataset is from Amazon Review Data (2018)
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.
Osmnx-examples - Usage examples, demos, and tutorials for OSMnx.
OSMnx Examples OSMnx is a Python package to work with street networks and other spatial data from OpenStreetMap: retrieve, model, analyze, and visuali
Awesome Graph Classification - A collection of important graph embedding, classification and representation learning papers with implementations.
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
Gans-in-action - Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
GANs in Action by Jakub Langr and Vladimir Bok List of available code: Chapter 2: Colab, Notebook Chapter 3: Notebook Chapter 4: Notebook Chapter 6: C
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai
Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
PyTorch-Multi-Style-Transfer - Neural Style and MSG-Net
PyTorch-Style-Transfer This repo provides PyTorch Implementation of MSG-Net (ours) and Neural Style (Gatys et al. CVPR 2016), which has been included
Speech-Emotion-Analyzer - The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)
Speech Emotion Analyzer The idea behind creating this project was to build a machine learning model that could detect emotions from the speech we have
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models
Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor
TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow
TensorFlow 101: Introduction to Deep Learning I have worked all my life in Machine Learning, and I've never seen one algorithm knock over its benchmar
Saliency - Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).
Saliency Methods 🔴 Now framework-agnostic! (Example core notebook) 🔴 🔗 For further explanation of the methods and more examples of the resulting ma
Fewshot-face-translation-GAN - Generative adversarial networks integrating modules from FUNIT and SPADE for face-swapping.
Few-shot face translation A GAN based approach for one model to swap them all. The table below shows our priliminary face-swapping results requiring o
Transformer - A TensorFlow Implementation of the Transformer: Attention Is All You Need
[UPDATED] A TensorFlow Implementation of Attention Is All You Need When I opened this repository in 2017, there was no official code yet. I tried to i
Tensorflow-Project-Template - A best practice for tensorflow project template architecture.
Tensorflow Project Template A simple and well designed structure is essential for any Deep Learning project, so after a lot of practice and contributi
Conversational-AI-ChatBot - Intelligent ChatBot built with Microsoft's DialoGPT transformer to make conversations with human users!
Conversational AI ChatBot Intelligent ChatBot built with Microsoft's DialoGPT transformer to make conversations with human users! In this project? Thi
Public repository containing materials used for Feed Forward (FF) Neural Networks article.
Art041_NN_Feed_Forward Public repository containing materials used for Feed Forward (FF) Neural Networks article. -- Illustration of a very simple Fee
Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.
Cancer-and-Tumor-Detection-Using-Inception-model In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks
SPT_LSA_ViT - Implementation for Visual Transformer for Small-size Datasets
Vision Transformer for Small-Size Datasets Seung Hoon Lee and Seunghyun Lee and Byung Cheol Song | Paper Inha University Abstract Recently, the Vision
Image-popularity-score - A novel deep regression method for image scoring.
Image-popularity-score - A novel deep regression method for image scoring.
BRNet - code for Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss function
BRNet code for "Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss func
CS5242_2021 - Neural Networks and Deep Learning, NUS CS5242, 2021
CS5242_2021 Neural Networks and Deep Learning, NUS CS5242, 2021 Cloud Machine #1 : Google Colab (Free GPU) Follow this Notebook installation : https:/
Siamese-nn-semantic-text-similarity - A repository containing comprehensive Neural Networks based PyTorch implementations for the semantic text similarity task
Siamese Deep Neural Networks for Semantic Text Similarity PyTorch A repository c
Self Governing Neural Networks (SGNN): the Projection Layer
Self Governing Neural Networks (SGNN): the Projection Layer A SGNN's word projections preprocessing pipeline in scikit-learn In this notebook, we'll u
Neural-fractal - Create Fractals Using Complex-Valued Neural Networks!
Neural Fractal Create Fractals Using Complex-Valued Neural Networks! Home Page Features Define Dynamical Systems Using Complex-Valued Neural Networks
Offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation
Shunted Transformer This is the offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation by Sucheng Ren, Daquan Zhou, Shengf
PyTorch Implementation of SSTNs for hyperspectral image classifications from the IEEE T-GRS paper "Spectral-Spatial Transformer Network for Hyperspectral Image Classification: A FAS Framework."
PyTorch Implementation of SSTN for Hyperspectral Image Classification Paper links: SSTN published on IEEE T-GRS. Also, you can directly find the imple
Python implementation of "Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation"
MIPNet: Multi-Instance Pose Networks This repository is the official pytorch python implementation of "Multi-Instance Pose Networks: Rethinking Top-Do
AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning Source code for AISTATS 2019 paper: Confidence-based Graph Convolutional Ne
Training neural models with structured signals.
Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured
Decensoring Hentai with Deep Neural Networks. Formerly named DeepMindBreak.
DeepCreamPy Decensoring Hentai with Deep Neural Networks. Formerly named DeepMindBreak. A deep learning-based tool to automatically replace censored a
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"
SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th
Pretraining on Dynamic Graph Neural Networks
Pretraining on Dynamic Graph Neural Networks Our article is PT-DGNN and the code is modified based on GPT-GNN Requirements python 3.6 Ubuntu 18.04.5 L
An implementation of Deep Graph Infomax (DGI) in PyTorch
DGI Deep Graph Infomax (Veličković et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom
Unsupervised Attributed Multiplex Network Embedding (AAAI 2020)
Unsupervised Attributed Multiplex Network Embedding (DMGI) Overview Nodes in a multiplex network are connected by multiple types of relations. However
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning
Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu
The official pytorch implementation of ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias
ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias Introduction | Updates | Usage | Results&Pretrained Models | Statement | Intr
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation Where we are ? 12.27 目前和原论文仍有1%左右得差距,但已经力压很多SOTA了 ckpt__448_epoch_25.pth mIoU
Variable Transformer Calculator
✠ VASCO - VAriable tranSformer CalculatOr Software que calcula informações de transformadores feita para a matéria de "Conversão Eletromecânica de Ene
Python wrapper for Synoptic Data API. Retrieve data from thousands of mesonet stations and networks. Returns JSON from Synoptic as Pandas DataFrame
☁ Synoptic API for Python (unofficial) The Synoptic Mesonet API (formerly MesoWest) gives you access to real-time and historical surface-based weather
The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
Block Modeling-Guided Graph Convolutional Neural Networks This repository contains the demo code of the paper: Block Modeling-Guided Graph Convolution
Official release of MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer axriv: http://arxiv.org/abs/2112.13513
MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis This is the official page of the MSHT with its experimental script and records. We de
Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm
Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation.
Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training
PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be
Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa
Deeper insights into graph convolutional networks for semi-supervised learning
deeper_insights_into_GCNs Deeper insights into graph convolutional networks for semi-supervised learning References data and utils.py come from Implem
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels"
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels" Please refer to htt
[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages
DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program
Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.
Official PyTorch implementation of the paper: "Self-Supervised Relational Reasoning for Representation Learning" (2020), Patacchiola, M., and Storkey,
AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video Recognition
AdaFocusV2 This repo contains the official code and pre-trained models for AdaFo
Unofficial TensorFlow implementation of the Keyword Spotting Transformer model
Keyword Spotting Transformer This is the unofficial TensorFlow implementation of the Keyword Spotting Transformer model. This model is used to train o
MeerKAT radio telescope simulation package. Built to simulate multibeam antenna data.
MeerKATgen MeerKAT radio telescope simulation package. Designed with performance in mind and utilizes Just in time compile (JIT) and XLA backed vectro
TensorFlow implementation of "Attention is all you need (Transformer)"
[TensorFlow 2] Attention is all you need (Transformer) TensorFlow implementation of "Attention is all you need (Transformer)" Dataset The MNIST datase
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis Jungil Kong, Jaehyeon Kim, Jaekyoung Bae In our paper, we p
PyTorch Implementation for Deep Metric Learning Pipelines
Easily Extendable Basic Deep Metric Learning Pipeline Karsten Roth ([email protected]), Biagio Brattoli ([email protected]) When using thi
XViT - Space-time Mixing Attention for Video Transformer
XViT - Space-time Mixing Attention for Video Transformer This is the official implementation of the XViT paper: @inproceedings{bulat2021space, title
Implementation of Memory-Efficient Neural Networks with Multi-Level Generation, ICCV 2021
Memory-Efficient Multi-Level In-Situ Generation (MLG) By Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen and David Z. Pan
Machine Learning Course Project, IMDB movie review sentiment analysis by lstm, cnn, and transformer
IMDB Sentiment Analysis This is the final project of Machine Learning Courses in Huazhong University of Science and Technology, School of Artificial I
Using GNU Radio and HackRF One to Receive, Analyze and Send ASK/OOK signals
play_with_ask NIS-8016 Lab A code: Recv.grc/py: Receive signals and match with ASK button using HackRF and GNU radio. I use AM demod block(can also in
Characterizing possible failure modes in physics-informed neural networks.
Characterizing possible failure modes in physics-informed neural networks This repository contains the PyTorch source code for the experiments in the
PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.
ALiBi PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. Quickstart Clone this reposit
A website which allows you to play with the GPT-2 transformer
transformers A website which allows you to play with the GPT-2 model Built with ❤️ by raphtlw Table of contents Model Setup About Contributors Model T
Tensor-Based Quantum Machine Learning
TensorLy_Quantum TensorLy-Quantum is a Python library for Tensor-Based Quantum Machine Learning that builds on top of TensorLy and PyTorch. Website: h
Tensorflow implementation for "Improved Transformer for High-Resolution GANs" (NeurIPS 2021).
HiT-GAN Official TensorFlow Implementation HiT-GAN presents a Transformer-based generator that is trained based on Generative Adversarial Networks (GA
A Pytorch Implementation of Domain adaptation of object detector using scissor-like networks
A Pytorch Implementation of Domain adaptation of object detector using scissor-like networks Please follow Faster R-CNN and DAF to complete the enviro