8658 Repositories
Python Road-Crack-Detection-Using-Deep-Learning-Methods Libraries
A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised Learning
LABES This is the code for EMNLP 2020 paper "A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised L
MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification
MixText This repo contains codes for the following paper: Jiaao Chen, Zichao Yang, Diyi Yang: MixText: Linguistically-Informed Interpolation of Hidden
Datasets for new state-of-the-art challenge in disentanglement learning
High resolution disentanglement datasets This repository contains the Falcor3D and Isaac3D datasets, which present a state-of-the-art challenge for co
implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning"
MarginGAN This repository is the implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning". 1."preliminary" is the imp
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
Good Semi-Supervised Learning That Requires a Bad GAN
Good Semi-Supervised Learning that Requires a Bad GAN This is the code we used in our paper Good Semi-supervised Learning that Requires a Bad GAN Ziha
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
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
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs MATLAB implementation of the paper: P. Mercado, F. Tudisco, and M. Hein,
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
Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Learning with Nonignorable Nonresponses‘
Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear
A Flexible Generative Framework for Graph-based Semi-supervised Learning (NeurIPS 2019)
G3NN This repo provides a pytorch implementation for the 4 instantiations of the flexible generative framework as described in the following paper: A
Meta Learning for Semi-Supervised Few-Shot Classification
few-shot-ssl-public Code for paper Meta-Learning for Semi-Supervised Few-Shot Classification. [arxiv] Dependencies cv2 numpy pandas python 2.7 / 3.5+
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
Scaling and Benchmarking Self-Supervised Visual Representation Learning
FAIR Self-Supervision Benchmark is deprecated. Please see VISSL, a ground-up rewrite of benchmark in PyTorch. FAIR Self-Supervision Benchmark This cod
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*
CCCL: Contrastive Cascade Graph Learning.
CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr
ViberExport - Export messages from Viber messenger using viber.db file
📲 ViberExport Export messages from Viber messenger using viber.db file ⚡ Usage:
This is a scalable system that reads messages from public Telegram channels using Telethon and stores the data in a PostgreSQL database.
This is a scalable system that reads messages from public Telegram channels using Telethon and stores the data in a PostgreSQL database. Its original intention is to monitor cryptocurrency related channels, but it can be configured to read any Telegram data that is accessible through the API.
Memory-efficient optimum einsum using opt_einsum planning and PyTorch kernels.
opt-einsum-torch There have been many implementations of Einstein's summation. numpy's numpy.einsum is the least efficient one as it only runs in sing
⭐️ Pyro String Generator ⭐️ Genrate String Session Using this bot.Made by TeamUltronX 🔥
⭐️ Pyro String Generator ⭐️ Genrate String Session Using this bot.Made by TeamUltronX 🔥 Configs: API_HASH Get from Here. API_ID Get from Here. API_KE
Personal implementation of paper "Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval"
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval This repo provides personal implementation of paper Approximate Ne
Ecco is a python library for exploring and explaining Natural Language Processing models using interactive visualizations.
Visualize, analyze, and explore NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).
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
Beibo is a Python library that uses several AI prediction models to predict stocks returns over a defined period of time.
Beibo is a Python library that uses several AI prediction models to predict stocks returns over a defined period of time.
Remote sensing change detection using PaddlePaddle
Change Detection Laboratory Developing and benchmarking deep learning-based remo
Run CodeServer on Google Colab using Inlets in less than 60 secs using your own domain.
Inlets Colab Run CodeServer on Colab using Inlets in less than 60 secs using your own domain. Features Optimized for Inlets/InletsPro Use your own Cus
The code of Zero-shot learning for low-light image enhancement based on dual iteration
Zero-shot-dual-iter-LLE The code of Zero-shot learning for low-light image enhancement based on dual iteration. You can get the real night image tests
Mixup for Supervision, Semi- and Self-Supervision Learning Toolbox and Benchmark
OpenSelfSup News Downstream tasks now support more methods(Mask RCNN-FPN, RetinaNet, Keypoints RCNN) and more datasets(Cityscapes). 'GaussianBlur' is
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
Graph Representation Learning via Graphical Mutual Information Maximization
GMI (Graphical Mutual Information) Graph Representation Learning via Graphical Mutual Information Maximization (Peng Z, Huang W, Luo M, et al., WWW 20
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
Contrastive Learning of Structured World Models
Contrastive Learning of Structured World Models This repository contains the official PyTorch implementation of: Contrastive Learning of Structured Wo
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
Contrastive Multi-View Representation Learning on Graphs
Contrastive Multi-View Representation Learning on Graphs This work introduces a self-supervised approach based on contrastive multi-view learning to l
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
Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"
Subg-Con Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning (Jiao et al., ICDM 2020): https://arxiv.org/abs/2009.10273 Over
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
Pytorch implementation of SELF-ATTENTIVE VAD, ICASSP 2021
SELF-ATTENTIVE VAD: CONTEXT-AWARE DETECTION OF VOICE FROM NOISE (ICASSP 2021) Pytorch implementation of SELF-ATTENTIVE VAD | Paper | Dataset Yong Rae
A curated list of awesome Model-Based RL resources
Awesome Model-Based Reinforcement Learning This is a collection of research papers for model-based reinforcement learning (mbrl). And the repository w
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
Improving Object Detection by Estimating Bounding Box Quality Accurately
Improving Object Detection by Estimating Bounding Box Quality Accurately Abstrac
Indonesia's negative news detection using gaussian naive bayes with Django+Scikir Learn
Introduction Indonesia's negative news detection using gaussian naive bayes build with Django and Scikit Learn. There is also any features, are: Input
In this work, we will implement some basic but important algorithm of machine learning step by step.
WoRkS continued English 中文 Français Probability Density Estimation-Non-Parametric Methods(概率密度估计-非参数方法) 1. Kernel / k-Nearest Neighborhood Density Est
Several implementations of classical games (ex: FlappyBird, Minesweeper etc.) using Python (pygame)
Mini Games with Pygame This projects implement several classic and popular games in Python, using python package -- pygame. Currently, 4 games are alr
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
A bulk pdf generator. This application can generate PDFs in bulk by using just one click.
A bulk html pdf generator. This application can generate PDFs in bulk by using just one click. Screenshots Requirements 🧱 Your system must have the f
Finite difference solution of 2D Poisson equation. Can handle Dirichlet, Neumann and mixed boundary conditions.
Poisson-solver-2D Finite difference solution of 2D Poisson equation Current version can handle Dirichlet, Neumann, and mixed (combination of Dirichlet
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
Designed a system that can efficiently sort recyclables and transfer them to corresponding bins using Python, a Raspberry Pi, and Quanser Labs.
System for Sorting and Recycling Containers - Project 3 Table of contents Overview The challenge Screenshot My process Built with Code snippets What I
A minimal open source mtg-like tcg game made in python that can be played on a terminal emulator using a keyboard.
TCG-TERM Project state: 🔧 🚧 🚧 🚧 Incomplete, In development 🚧 🚧 🚧 👷 (Keep in mind that at the moment, This project is currently undone, and wil
Ansible tools for operating and managing fleets of Blinksticks in harmony using the Blinkstick Python library.
Ansible tools for operating and managing fleets of Blinksticks in harmony using the Blinkstick Python library.
Python library for loading and using triangular meshes.
Trimesh is a pure Python (2.7-3.4+) library for loading and using triangular meshes with an emphasis on watertight surfaces. The goal of the library i
Simple python 3D vector3 math library wrapping some types from GLM library using pybind11.
vmath Simple python 3D vector3 math library wrapping some types from GLM library using pybind11. Description Both pure python version and C++ version
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
Gmail account using brute force attack
Programmed in Python | PySimpleGUI Gmail Hack Python script with PySimpleGUI for hack gmail account using brute force attack If you like it give it
Python library for parsing resumes using natural language processing and machine learning
CVParser Python library for parsing resumes using natural language processing and machine learning. Setup Installation on Linux and Mac OS Follow the
A simpler way to make forms, surveys, and reaction input using discord.py.
discord-ext-forms An easier way to make forms and surveys in discord.py. This module is a very simple way to ask questions and create complete forms i
3D-Lorenz-Attractor-simulation-with-python
3D-Lorenz-Attractor-simulation-with-python Animação 3D da trajetória do Atrator de Lorenz, implementada em Python usando o método de Runge-Kutta de 4ª
🔀 Visual Room Rearrangement
AI2-THOR Rearrangement Challenge Welcome to the 2021 AI2-THOR Rearrangement Challenge hosted at the CVPR'21 Embodied-AI Workshop. The goal of this cha
A timer for bird lovers, plays a random birdcall while displaying its image and info.
Birdcall Timer A timer for bird lovers. Siriema hatchling by Junior Peres Junior Background My partner needed a customizable timer for sitting and sta
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
This is an Airport Scheduling Time table implemented using Genetic Algorithm
This is an Airport Scheduling Time table implemented using Genetic Algorithm In this The scheduling is performed on the basisi of that no two Air planes are arriving or departing at the same runway at the same time and day there are total of 4 Airplanes 3 and 3 Runways.
A webpage that utilizes machine learning to extract sentiments from tweets.
Tweets_Classification_Webpage The goal of this project is to be able to predict what rating customers on social media platforms would give to products
Made with pygame. Multiplayer game using socket module and threading.
Rock Paper Scissor made with python-pygame. Poorly made, as a beginner in programming. Multiplayer with server code and client code provided.
A telegram bot script for generating session string using pyrogram and telethon on Telegram bot
String-session-Bot Telegram Bot to generate Pyrogram and Telethon String Session. A star ⭐ from you means a lot to us! Usage Deploy to Heroku Tap on a
Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch
CutPaste CutPaste: image from paper Unofficial implementation of Google's "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization"
Code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods."
pv_predict_unet-lstm Code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods." IEEE Transactions
Simple Login Logout System using Django, JavaScript and ajax.
Djanog-UserAuthenticationSystem Technology Use #version Python 3.9.5 Django 3.2.7 JavaScript --- Ajax Validation --- Login and Logout Functionality, A
Align and Prompt: Video-and-Language Pre-training with Entity Prompts
ALPRO Align and Prompt: Video-and-Language Pre-training with Entity Prompts [Paper] Dongxu Li, Junnan Li, Hongdong Li, Juan Carlos Niebles, Steven C.H
An image validator using FastAPI.
fast_api_image_validator An image validator using FastAPI.
A similarity measurer on two programming assignments on Online Judge.
A similarity measurer on two programming assignments on Online Judge. Algorithm implementation details are at here. Install Recommend OS: Ubuntu 20.04
N-Omniglot is a large neuromorphic few-shot learning dataset
N-Omniglot [Paper] || [Dataset] N-Omniglot is a large neuromorphic few-shot learning dataset. It reconstructs strokes of Omniglot as videos and uses D
In this project, we develop a face recognize platform based on MTCNN object-detection netcwork and FaceNet self-supervised network.
模式识别大作业——人脸检测与识别平台 本项目是一个简易的人脸检测识别平台,提供了人脸信息录入和人脸识别的功能。前端采用 html+css+js,后端采用 pytorch,
Deep Semisupervised Multiview Learning With Increasing Views (IEEE TCYB 2021, PyTorch Code)
Deep Semisupervised Multiview Learning With Increasing Views (ISVN, IEEE TCYB) Peng Hu, Xi Peng, Hongyuan Zhu, Liangli Zhen, Jie Lin, Huaibai Yan, Dez
A Blender add-on to create interesting meshes using symmetry
Procedural Symmetries This Blender add-on automates the process of iteratively applying a set of reflection planes to a base mesh. The result will con
Command line interface for sending email using SMTP (ships with Gmail configuration).
mailsend Description Lightweight command line interface for sending email using SMTP. Default configuration is set for Gmail (smtp.gmail.com at port 5
Python wrapper for Xeno-canto API 2.0. Enables downloading bird data with one command line
Python wrapper for Xeno-canto API 2.0. Enables downloading bird data with one command line. Supports multithreading
Python scripts aim to use a Random Forest machine learning algorithm to predict the water affinity of Metal-Organic Frameworks
The following Python scripts aim to use a Random Forest machine learning algorithm to predict the water affinity of Metal-Organic Frameworks (MOFs). The training set is extracted from the Cambridge Structural Database and the CoRE_MOF 2019 dataset.
This mini project showcase how to build and debug Apache Spark application using Python
Spark app can't be debugged using normal procedure. This mini project showcase how to build and debug Apache Spark application using Python programming language. There are also options to run Spark application on Spark container
Place holder for HOPE: a human-centric and task-oriented MT evaluation framework using professional post-editing
HOPE: A Task-Oriented and Human-Centric Evaluation Framework Using Professional Post-Editing Towards More Effective MT Evaluation Place holder for dat
Out-of-Distribution Generalization of Chest X-ray Using Risk Extrapolation
OoD_Gen-Chest_Xray Out-of-Distribution Generalization of Chest X-ray Using Risk Extrapolation Requirements (Installations) Install the following libra
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 repository of IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSUMPTION.
IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSUMPTION This is the official repository of IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSU
For storing the complete exploration of Visual Question Answering for our B.Tech Project
Multi-Image vqa @authors: Akhilesh, Janhavi, Harsh Paper summary, Ideas tried and their corresponding results: on wiki Other discussions: on discussio
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
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).
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
Source code of the "Graph-Bert: Only Attention is Needed for Learning Graph Representations" paper
Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We
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