4318 Repositories
Python deep-neural-network Libraries
PySOT - SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.
PySOT is a software system designed by SenseTime Video Intelligence Research team. It implements state-of-the-art single object tracking algorit
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🔥
Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano
Please read the blog post that goes with this code! Jupyter Notebook Setup System Requirements: Python, pip (Optional) virtualenv To start the Jupyter
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
PConv-Keras - Unofficial implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions". Try at: www.fixmyphoto.ai
Partial Convolutions for Image Inpainting using Keras Keras implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions", https
TensorFlow-LiveLessons - "Deep Learning with TensorFlow" LiveLessons
TensorFlow-LiveLessons Note that the second edition of this video series is now available here. The second edition contains all of the content from th
Coursera - Quiz & Assignment of Coursera
Coursera Assignments This repository is aimed to help Coursera learners who have difficulties in their learning process. The quiz and programming home
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
Aws-machine-learning-university-accelerated-tab - Machine Learning University: Accelerated Tabular Data Class
Machine Learning University: Accelerated Tabular Data Class This repository contains slides, notebooks, and datasets for the Machine Learning Universi
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
Nerf pl - NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning
nerf_pl Update: an improved NSFF implementation to handle dynamic scene is open! Update: NeRF-W (NeRF in the Wild) implementation is added to nerfw br
Python Deep Dive Course - Accompanying Materials
Python Deep Dive Various Jupyter notebooks and Python sources associated with my Udemy Python 3 Deep Dive course series: Part 1: Mainly functional pro
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Keras Realtime Multi-Person Pose Estimation - Keras version of Realtime Multi-Person Pose Estimation project
This repository has become incompatible with the latest and recommended version of Tensorflow 2.0 Instead of refactoring this code painfully, I create
Finetune alexnet with tensorflow - Code for finetuning AlexNet in TensorFlow = 1.2rc0
Finetune AlexNet with Tensorflow Update 15.06.2016 I revised the entire code base to work with the new input pipeline coming with TensorFlow = versio
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
Detectron2-FC a fast construction platform of neural network algorithm based on detectron2
What is Detectron2-FC Detectron2-FC a fast construction platform of neural network algorithm based on detectron2. We have been working hard in two dir
Intro-to-dl - Resources for "Introduction to Deep Learning" course.
Introduction to Deep Learning course resources https://www.coursera.org/learn/intro-to-deep-learning Running on Google Colab (tested for all weeks) Go
Video2x - A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K, SRMD and RealSR.
Official Discussion Group (Telegram): https://t.me/video2x A Discord server is also available. Please note that most developers are only on Telegram.
A Tensorflow implementation of CapsNet based on Geoffrey Hinton's paper Dynamic Routing Between Capsules
CapsNet-Tensorflow A Tensorflow implementation of CapsNet based on Geoffrey Hinton's paper Dynamic Routing Between Capsules Notes: The current version
Client - 🔥 A tool for visualizing and tracking your machine learning experiments
Weights and Biases Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to produ
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Created by Charles R. Qi, Hao Su, Kaichun Mo, Leonidas J. Guibas from Sta
Generate image analogies using neural matching and blending
neural image analogies This is basically an implementation of this "Image Analogies" paper, In our case, we use feature maps from VGG16. The patch mat
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
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
Simple-Neural-Network From Scratch in Python
Simple-Neural-Network From Scratch in Python This is a simple Neural Network created without any Machine Learning Libraries. The only dependencies are
Losslandscapetaxonomy - Taxonomizing local versus global structure in neural network loss landscapes
Taxonomizing local versus global structure in neural network loss landscapes Int
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
Omdena-abuja-anpd - Automatic Number Plate Detection for the security of lives and properties using Computer Vision.
Omdena-abuja-anpd - Automatic Number Plate Detection for the security of lives and properties using Computer Vision.
Time-series-deep-learning - Developing Deep learning LSTM, BiLSTM models, and NeuralProphet for multi-step time-series forecasting of stock price.
Stock Price Prediction Using Deep Learning Univariate Time Series Predicting stock price using historical data of a company using Neural networks for
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
Breast Cancer Detection 🔬 ITI "AI_Pro" Graduation Project
BreastCancerDetection - This program is designed to predict two severity of abnormalities associated with breast cancer cells: benign and malignant. Mammograms from MIAS is preprocessed and features are extracted using the pre-trained CNN.
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:/
Locationinfo - A script helps the user to show network information such as ip address
Description This script helps the user to show network information such as ip ad
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
Ppq - A powerful offline neural network quantization tool with custimized IR
PPL Quantization Tool(PPL 量化工具) PPL Quantization Tool (PPQ) is a powerful offlin
HAR-stacked-residual-bidir-LSTMs - Deep stacked residual bidirectional LSTMs for HAR
HAR-stacked-residual-bidir-LSTM The project is based on this repository which is presented as a tutorial. It consists of Human Activity Recognition (H
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto
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
A Survey on Deep Learning Technique for Video Segmentation
A Survey on Deep Learning Technique for Video Segmentation A Survey on Deep Learning Technique for Video Segmentation Wenguan Wang, Tianfei Zhou, Fati
SOTA easy to use PyTorch-based DL training library
Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open
“Robust Lightweight Facial Expression Recognition Network with Label Distribution Training”, AAAI 2021.
EfficientFace Zengqun Zhao, Qingshan Liu, Feng Zhou. "Robust Lightweight Facial Expression Recognition Network with Label Distribution Training". AAAI
PyTorch Lightning + Hydra. A feature-rich template for rapid, scalable and reproducible ML experimentation with best practices. ⚡🔥⚡
Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re
A library for uncertainty quantification based on PyTorch
Torchuq [logo here] TorchUQ is an extensive library for uncertainty quantification (UQ) based on pytorch. TorchUQ currently supports 10 representation
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
The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode
DeFi wallet on Chia Network.
DeFi wallet on Chia Network.
Bulk2Space is a spatial deconvolution method based on deep learning frameworks
Bulk2Space Spatially resolved single-cell deconvolution of bulk transcriptomes using Bulk2Space Bulk2Space is a spatial deconvolution method based on
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
A state-of-the-art semi-supervised method for image recognition
Mean teachers are better role models Paper ---- NIPS 2017 poster ---- NIPS 2017 spotlight slides ---- Blog post By Antti Tarvainen, Harri Valpola (The
Ladder network is a deep learning algorithm that combines supervised and unsupervised learning
This repository contains source code for the experiments in a paper titled Semi-Supervised Learning with Ladder Networks by A Rasmus, H Valpola, M Hon
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation.
Training Script for Reuse-VOS This code implementation of CVPR 2021 paper : Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Vi
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations, CVPR 2019 (Oral)
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations The code of: Weakly Supervised Learning of Instance Segmentation with I
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018
Adversarial Learning for Semi-supervised Semantic Segmentation This repo is the pytorch implementation of the following paper: Adversarial Learning fo
Weakly- and Semi-Supervised Panoptic Segmentation (ECCV18)
Weakly- and Semi-Supervised Panoptic Segmentation by Qizhu Li*, Anurag Arnab*, Philip H.S. Torr This repository demonstrates the weakly supervised gro
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR 2018).
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR2018) By Zilong Huang, Xinggang Wang, Jiasi Wang, Wenyu Liu and J
Weakly-supervised object detection.
Wetectron Wetectron is a software system that implements state-of-the-art weakly-supervised object detection algorithms. Project CVPR'20, ECCV'20 | Pa
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
COResets and Data Subset selection Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order
PyTorch implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose
Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The official PyTorch implementation of Neural View S
A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
Deep SAD: A Method for Deep Semi-Supervised Anomaly Detection This repository provides a PyTorch implementation of the Deep SAD method presented in ou
Implementation of ICLR 2020 paper "Revisiting Self-Training for Neural Sequence Generation"
Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi
Neural network sequence labeling model
Sequence labeler This is a neural network sequence labeling system. Given a sequence of tokens, it will learn to assign labels to each token. Can be u
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model Baris Gecer 1, Binod Bhattarai 1
Class-Attentive Diffusion Network for Semi-Supervised Classification [AAAI'21] (official implementation)
Class-Attentive Diffusion Network for Semi-Supervised Classification Official Implementation of AAAI 2021 paper Class-Attentive Diffusion Network for
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
SemiNAS: Semi-Supervised Neural Architecture Search
SemiNAS: Semi-Supervised Neural Architecture Search This repository contains the code used for Semi-Supervised Neural Architecture Search, by Renqian
Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
Semi-supervised Deep Kernel Learning This is the code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data
Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters.
Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters. Overview This project is a Torch implementation for our CVPR 2016 paper
PyTorch implementation for Graph Contrastive Learning with Augmentations
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
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
Remote sensing change detection using PaddlePaddle
Change Detection Laboratory Developing and benchmarking deep learning-based remo
A simplistic and efficient pure-python neural network library from Phys Whiz with CPU and GPU support.
A simplistic and efficient pure-python neural network library from Phys Whiz with CPU and GPU support.
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
PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE).
GRACE The official PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE). For a thorough resource collection of self-superv
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
Heterogeneous Deep Graph Infomax
Heterogeneous-Deep-Graph-Infomax Parameter Setting: HDGI-A: Node-level dimension: 16 Attention head: 4 Semantic-level attention vector: 8 learning rat
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
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
Introduction QRec is a Python framework for recommender systems (Supported by Python 3.7.4 and Tensorflow 1.14+) in which a number of influential and
ncnn is a high-performance neural network inference framework optimized for the mobile platform
ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme
Deep Hedging Demo - An Example of Using Machine Learning for Derivative Pricing.
Deep Hedging Demo Pricing Derivatives using Machine Learning 1) Jupyter version: Run ./colab/deep_hedging_colab.ipynb on Colab. 2) Gui version: Run py
Minimal implementation and experiments of "No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging".
No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging Minimal implementation and experiments of "No-Transaction Band N
PyTorch-based framework for Deep Hedging
PFHedge: Deep Hedging in PyTorch PFHedge is a PyTorch-based framework for Deep Hedging. PFHedge Documentation Neural Network Architecture for Efficien
Official implementation of CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21
CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21 For more information, check out the paper on [arXiv]. Training with different
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥
ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage
Exploiting CVE-2021-44228 in Unifi Network Application for remote code execution and more
Log4jUnifi Exploiting CVE-2021-44228 in Unifi Network Application for remote cod
Numerical Methods with Python, Numpy and Matplotlib
Numerical Bric-a-Brac Collections of numerical techniques with Python and standard computational packages (Numpy, SciPy, Numba, Matplotlib ...). Diffe
Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs.
Lunar Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs. About Lunar can be modified to work
Retrieve and analysis data from SDSS (Sloan Digital Sky Survey)
Author: Behrouz Safari License: MIT sdss A python package for retrieving and analysing data from SDSS (Sloan Digital Sky Survey) Installation Install
Minecraft Multi-Server Pinger Discord Embed
Minecraft Network Pinger Minecraft Multi-Server Pinger Discord Embed What does this bot do? It sends an embed and uses mcsrvstat API and checks if the
Python implementation of O-OFDMNet, a deep learning-based optical OFDM system,
O-OFDMNet This includes Python implementation of O-OFDMNet, a deep learning-based optical OFDM system, which uses neural networks for signal processin