2173 Repositories
Python Self-Supervised-Music-Analysis Libraries
Doing bayesian data analysis - Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke
Doing_bayesian_data_analysis This repository contains the Python version of the R programs described in the great book Doing bayesian data analysis (f
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
CarND-LaneLines-P1 - Lane Finding Project for Self-Driving Car ND
Finding Lane Lines on the Road Overview When we drive, we use our eyes to decide where to go. The lines on the road that show us where the lanes are a
Kaggle-titanic - A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.
Kaggle-titanic This is a tutorial in an IPython Notebook for the Kaggle competition, Titanic Machine Learning From Disaster. The goal of this reposito
Statistical-Rethinking-with-Python-and-PyMC3 - Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath
Statistical Rethinking with Python and PyMC3 This repository has been deprecated in favour of this one, please check that repository for updates, for
Checkov is a static code analysis tool for infrastructure-as-code.
Checkov - Prevent cloud misconfigurations during build-time for Terraform, Cloudformation, Kubernetes, Serverless framework and other infrastructure-as-code-languages with Checkov by Bridgecrew.
Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities
Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities. This is aimed at those looking to get into the field of Data Science or those who are already in the field and looking to solve a real-world project with python.
DankMemer-Farmer - Autofarm Self-Bot for Discord bot Named Dankmemer.
DankMemer-Farmer Autofarm Self-Bot for Discord bot Named Dankmemer. Warning We are not responsible if you got banned, since "self-bots" outside of the
TwitterMusicBot - A Twitter bot with Spotify integration.
A Twitter Music Bot 🤖 🎵 🎶 I created this project to learn more about APIs, so it only works for student purposes. Initially, delving into the Spoti
Customer-Transaction-Analysis - This analysis is based on a synthesised transaction dataset containing 3 months worth of transactions for 100 hypothetical customers.
Customer-Transaction-Analysis - This analysis is based on a synthesised transaction dataset containing 3 months worth of transactions for 100 hypothetical customers. It contains purchases, recurring transactions, and salary transactions. The dataset is designed to simulate realistic transaction behaviours that are observed in ANZ’s real transaction data.
Ethone-Selfbot - Open Source Discord Self-Bot, written in discord.py
Ethone SB Table of contents Newest open-source Discord SelfBot with useful commands and easy documentation on how to add your own and change the exist
Vixtify - Python Controlled Music Player
Strumm Sound Playlist : Click me to listen Welcome to GitHub Pages You can use the editor on GitHub to maintain and preview the content for your websi
Twitter-Sentiment-Analysis - Twitter sentiment analysis for india's top online retailers(2019 to 2022)
Twitter-Sentiment-Analysis Twitter sentiment analysis for india's top online retailers(2019 to 2022) Project Overview : Sentiment Analysis helps us to
ShadowMusic - A Telegram Music Bot with proper functions written in Python with Pyrogram and Py-Tgcalls.
⭐️ Shadow Music ⭐️ A Telegram Music Bot written in Python using Pyrogram and Py-Tgcalls Ready to use method A Support Group, Updates Channel and ready
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
CodeAnalysis - Static Code Analysis: a code comprehensive analysis platform
TCA, Tencent Cloud Code Analysis English | 简体中文 What is TCA Tencent Cloud Code A
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 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
Code used for the results in the paper "ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning"
Code used for the results in the paper "ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning" Getting started Prerequisites CUD
A simple consistency training framework for semi-supervised image semantic segmentation
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation PseudoSeg is a simple consistency training framework for semi-supervised image semantic s
Semi-supervised semantic segmentation needs strong, varied perturbations
Semi-supervised semantic segmentation using CutMix and Colour Augmentation Implementations of our papers: Semi-supervised semantic segmentation needs
A PyTorch-based Semi-Supervised Learning (SSL) Codebase for Pixel-wise (Pixel) Vision Tasks
PixelSSL is a PyTorch-based semi-supervised learning (SSL) codebase for pixel-wise (Pixel) vision tasks. The purpose of this project is to promote the
Learning Saliency Propagation for Semi-supervised Instance Segmentation
Learning Saliency Propagation for Semi-supervised Instance Segmentation PyTorch Implementation This repository contains: the PyTorch implementation of
Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation, CVPR 2020 (Oral)
SEAM The implementation of Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentaion. You can also download the repos
Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT)
Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT) Paper, Project Page This repo contains the official implementation of CVPR
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing
CapsuleVOS This is the code for the ICCV 2019 paper CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing. Arxiv Link: https://a
Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019
USSS_ICCV19 Code for Universal Semi Supervised Semantic Segmentation accepted to ICCV 2019. Full Paper available at https://arxiv.org/abs/1811.10323.
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 Segmentation by Tensorflow.
Weakly Supervised Segmentation by Tensorflow. Implements semantic segmentation in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).
Implementation of " SESS: Self-Ensembling Semi-Supervised 3D Object Detection" (CVPR2020 Oral)
SESS: Self-Ensembling Semi-Supervised 3D Object Detection Created by Na Zhao from National University of Singapore Introduction This repository contai
Semi-supervised learning for object detection
Source code for STAC: A Simple Semi-Supervised Learning Framework for Object Detection STAC is a simple yet effective SSL framework for visual object
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
CSD: Consistency-based Semi-supervised learning for object Detection
CSD: Consistency-based Semi-supervised learning for object Detection (NeurIPS 2019) By Jisoo Jeong, Seungeui Lee, Jee-soo Kim, Nojun Kwak Installation
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
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdh
[CVPR'2020] DeepDeform: Learning Non-rigid RGB-D Reconstruction with Semi-supervised Data
DeepDeform (CVPR'2020) DeepDeform is an RGB-D video dataset containing over 390,000 RGB-D frames in 400 videos, with 5,533 optical and scene flow imag
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
Learning to Self-Train for Semi-Supervised Few-Shot
Learning to Self-Train for Semi-Supervised Few-Shot Classification This repository contains the TensorFlow implementation for NeurIPS 2019 Paper "Lear
Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition (NeurIPS 2019)
MLCR This is the source code for paper Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition. Xuesong Niu, Hu Han, Shiguang
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
Semi-SDP Semi-supervised parser for semantic dependency parsing.
Semi-SDP Semi-supervised parser for semantic dependency parsing. This repo contains the code used for the semi-supervised semantic dependency parser i
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
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
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
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,
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
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
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
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
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.
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
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
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
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
Rocks vc Userbot: A Telegram Bot Project That's Allow You To Play Audio And Video Music On Telegram Voice Chat Group
⭐️ Rocks VC Userbot ⭐️ Telegram Userbot To Play Audio And Video Song On VC Chat
Music library streaming app written in Flask & VueJS
djtaytay This is a little toy app made to explore Vue, brush up on my Python, and make a remote music collection accessable through a web interface. I
A module to get data about anime characters, news, info, lyrics and more.
Animec A module to get data about anime characters, news, info, lyrics and more. The module scrapes myanimelist to parse requested data. If you wish t
Simple discord bot by @merive 🤖
Parzibot Powerful and Useful Discord Bot on Python. The source code of the bot is available to everyone. Parzibot uses English language. This is free
Plotting and analysis tools for ARTIS simulations
Artistools Artistools is collection of plotting, analysis, and file format conversion tools for the ARTIS radiative transfer code. Installation First
Spatial Single-Cell Analysis Toolkit
Single-Cell Image Analysis Package Scimap is a scalable toolkit for analyzing spatial molecular data. The underlying framework is generalizable to spa
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
web application for flight log analysis & review
Flight Review This is a web application for flight log analysis. It allows users to upload ULog flight logs, and analyze them through the browser. It
A simple Python app to provide RPC for iTunes and the Music app. MacOS exclusive.
Ongaku You know, ongaku. A port of Ongaku to Python. Why? I don't know. A simple application providing the now playing state from iTunes (or the Music
A project in order to analyze user's favorite musics, artists and genre
Spotify-Wrapped This is a project about Spotify Wrapped (which is an extra option for premium accounts, but you don't need to be premium here) This pr
Spectral Analysis in Python
SPECTRUM : Spectral Analysis in Python contributions: Please join https://github.com/cokelaer/spectrum contributors: https://github.com/cokelaer/spect
Manage your XYZ Hub or HERE Data Hub spaces from Python.
XYZ Spaces for Python Manage your XYZ Hub or HERE Data Hub spaces and Interactive Map Layer from Python. FEATURED IN: Online Python Machine Learning C
A simple electrical network analyzer, BASED ON computer-aided design.
Electrical Network Analyzer A simple electrical network analyzer. Given the oriented graph of the electrical network (circut), BASED ON computer-aided
Telegram music & video bot direct play music
⚡ NOINOI MUSIC PLAYER 🎵 SUPERFAST MUSIC BOT WHO CAN DIRECT PLAY SONG ON TELEGRAM VOICE CHAT ALSO CAN PLAY VIDEO ON VOICE CHATS ✨ Heroku Deploy YOU CA
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"
Source code of AAAI 2022 paper "Towards End-to-End Image Compression and Analysis with Transformers".
Towards End-to-End Image Compression and Analysis with Transformers Source code of our AAAI 2022 paper "Towards End-to-End Image Compression and Analy
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,
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
Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism"
SUGAR Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism" Overview train.py: the cor
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
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
code for "Self-supervised edge features for improved Graph Neural Network training", arxivlink
Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.
A Self-Supervised Contrastive Learning Framework for Aspect Detection
AspDecSSCL A Self-Supervised Contrastive Learning Framework for Aspect Detection This repository is a pytorch implementation for the following AAAI'21
Self-Guided Contrastive Learning for BERT Sentence Representations
Self-Guided Contrastive Learning for BERT Sentence Representations This repository is dedicated for releasing the implementation of the models utilize