609 Repositories
Python kmeans-clustering-algorithm Libraries
My own Unicode compression algorithm
Zee Code ZCode is a custom compression algorithm I originally developed for a competition held for the Spring 2019 Datastructures and Algorithms cours
Python3 Implementation of (Subspace Constrained) Mean Shift Algorithm in Euclidean and Directional Product Spaces
(Subspace Constrained) Mean Shift Algorithms in Euclidean and/or Directional Product Spaces This repository contains Python3 code for the mean shift a
A rule learning algorithm for the deduction of syndrome definitions from time series data.
README This project provides a rule learning algorithm for the deduction of syndrome definitions from time series data. Large parts of the algorithm a
abess: Fast Best-Subset Selection in Python and R
abess: Fast Best-Subset Selection in Python and R Overview abess (Adaptive BEst Subset Selection) library aims to solve general best subset selection,
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
TumorInsight is a Brain Tumor Detection and Classification model built using RESNET50 architecture.
A Brain Tumor Detection and Classification Model built using RESNET50 architecture. The model is also deployed as a web application using Flask framework.
Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train format
ttopt Description Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train (TT) format and maximu
A solution to the 2D Ising model of ferromagnetism, implemented using the Metropolis algorithm
Solving the Ising model on a 2D lattice using the Metropolis Algorithm Introduction The Ising model is a simplified model of ferromagnetism, the pheno
A GUI visualization of QuickSort algorithm
QQuickSort A simple GUI visualization of QuickSort algorithm. It only uses PySide6, it does not have any other external dependency. How to run Install
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss (HDCWNet)
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss (HDCWNet) (
A collection of neat and practical data science and machine learning projects
Data Science A collection of neat and practical data science and machine learning projects Explore the docs » Report Bug · Request Feature Table of Co
A raw implementation of the nearest insertion algorithm to resolve TSP problems in a TXT format.
TSP-Nearest-Insertion A raw implementation of the nearest insertion algorithm to resolve TSP problems in a TXT format. Instructions Load a txt file wi
The code for paper Efficiently Solve the Max-cut Problem via a Quantum Qubit Rotation Algorithm
Quantum Qubit Rotation Algorithm Single qubit rotation gates $$ U(\Theta)=\bigotimes_{i=1}^n R_x (\phi_i) $$ QQRA for the max-cut problem This code wa
Source code for The Power of Many: A Physarum Swarm Steiner Tree Algorithm
Physarum-Swarm-Steiner-Algo Source code for The Power of Many: A Physarum Steiner Tree Algorithm Code implements ideas from the following papers: Sher
This folder contains the implementation of the multi-relational attribute propagation algorithm.
MrAP This folder contains the implementation of the multi-relational attribute propagation algorithm. It requires the package pytorch-scatter. Please
The implementation of FOLD-R++ algorithm
FOLD-R-PP The implementation of FOLD-R++ algorithm. The target of FOLD-R++ algorithm is to learn an answer set program for a classification task. Inst
CPC-big and k-means clustering for zero-resource speech processing
The CPC-big model and k-means checkpoints used in Analyzing Speaker Information in Self-Supervised Models to Improve Zero-Resource Speech Processing.
Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm.
Naive-Bayes Spam Classificator Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm. Main goal is to code a
A simple python program to sign text using either the RSA or ISRSAC algorithm with GUI built using tkinter library.
Digital Signatures using ISRSAC Algorithm A simple python program to sign text using either the RSA or ISRSAC algorithm with GUI built using tkinter l
A gui application to visualize various sorting algorithms using pure python.
Sorting Algorithm Visualizer A gui application to visualize various sorting algorithms using pure python. Language : Python 3 Libraries required Tkint
An implementation of the [Hierarchical (Sig-Wasserstein) GAN] algorithm for large dimensional Time Series Generation
Hierarchical GAN for large dimensional financial market data Implementation This repository is an implementation of the [Hierarchical (Sig-Wasserstein
Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE)
OG-SPACE Introduction Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE) is a computational framewo
Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution
unfoldedVBA Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution This repository contains the Pytorch implementation of the unrolled
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "
Semi-Supervised Signed Clustering Graph Neural Network (and Implementation of Some Spectral Methods)
SSSNET SSSNET: Semi-Supervised Signed Network Clustering For details, please read our paper. Environment Setup Overview The project has been tested on
This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022
CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC
Introduction to AI assignment 1 HCM University of Technology, term 211
Sokoban Bot Introduction to AI assignment 1 HCM University of Technology, term 211 Abstract This is basically a solver for Sokoban game using Breadth-
PyTorch implementation of DreamerV2 model-based RL algorithm
PyDreamer Reimplementation of DreamerV2 model-based RL algorithm in PyTorch. The official DreamerV2 implementation can be found here. Features ... Run
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination (ICCV 2021) Dataset License This work is l
A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search
A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search
Tribuo - A Java machine learning library
Tribuo - A Java prediction library (v4.1) Tribuo is a machine learning library in Java that provides multi-class classification, regression, clusterin
Short Program using Transavia's API to notify via email an user waiting for a flight at special dates and with the best price
Flight-Notifier Short Program using Transavia's API to notify via email an user waiting for a flight at special dates and with the best price Algorith
Neural network for recognizing the gender of people in photos
Neural Network For Gender Recognition How to test it? Install requirements.txt file using pip install -r requirements.txt command Run nn.py using pyth
using Machine Learning Algorithm to classification AppleStore application
AppleStore-classification-with-Machine-learning-Algo- using Machine Learning Algorithm to classification AppleStore application. the first step : 1: p
BASTA: The BAyesian STellar Algorithm
BASTA: BAyesian STellar Algorithm Current stable version: v1.0 Important note: BASTA is developed for Python 3.8, but Python 3.7 should work as well.
🧬 Training the car to do self-parking using a genetic algorithm
🧬 Training the car to do self-parking using a genetic algorithm
NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training
NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training
A Python Package for Portfolio Optimization using the Critical Line Algorithm
A Python Package for Portfolio Optimization using the Critical Line Algorithm
Implementation of linear CorEx and temporal CorEx.
Correlation Explanation Methods Official implementation of linear correlation explanation (linear CorEx) and temporal correlation explanation (T-CorEx
PyTorch implementation of DeepDream algorithm
neural-dream This is a PyTorch implementation of DeepDream. The code is based on neural-style-pt. Here we DeepDream a photograph of the Golden Gate Br
Implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTorch
Neural Distance Embeddings for Biological Sequences Official implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTo
8-puzzle-solver with UCS, ILS, IDA* algorithm
Eight Puzzle 8-puzzle-solver with UCS, ILS, IDA* algorithm pre-usage requirements python3 python3-pip virtualenv prepare enviroment virtualenv -p pyth
A Python Package for Portfolio Optimization using the Critical Line Algorithm
PyCLA A Python Package for Portfolio Optimization using the Critical Line Algorithm Getting started To use PyCLA, clone the repo and install the requi
ppo_pytorch_cpp - an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch
PPO Pytorch C++ This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment t
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte
Implements pytorch code for the Accelerated SGD algorithm.
AccSGD This is the code associated with Accelerated SGD algorithm used in the paper On the insufficiency of existing momentum schemes for Stochastic O
A Multilingual Latent Dirichlet Allocation (LDA) Pipeline with Stop Words Removal, n-gram features, and Inverse Stemming, in Python.
Multilingual Latent Dirichlet Allocation (LDA) Pipeline This project is for text clustering using the Latent Dirichlet Allocation (LDA) algorithm. It
🏃 Python Solutions of All Problems in FHC 2021 (In Progress)
FacebookHackerCup-2021 Python solutions of Facebook Hacker Cup 2021. Solution begins with * means it will get TLE in the largest data set (total compu
Vehicle Detection Using Deep Learning and YOLO Algorithm
VehicleDetection Vehicle Detection Using Deep Learning and YOLO Algorithm Dataset take or find vehicle images for create a special dataset for fine-tu
Simple algorithm search engine like google in python using function
Mini-Search-Engine-Like-Google I have created the simple algorithm search engine like google in python using function. I am matching every word with w
Stor is a community-driven green cryptocurrency based on a proof of space and time consensus algorithm.
Stor Blockchain Stor is a community-driven green cryptocurrency based on a proof of space and time consensus algorithm. For more information, see our
This repository contains a set of codes to run (i.e., train, perform inference with, evaluate) a diarization method called EEND-vector-clustering.
EEND-vector clustering The EEND-vector clustering (End-to-End-Neural-Diarization-vector clustering) is a speaker diarization framework that integrates
DataCLUE: 国内首个以数据为中心的AI测评(含模型分析报告)
DataCLUE 以数据为中心的AI测评(DataCLUE) DataCLUE: A Chinese Data-centric Language Evaluation Benchmark 内容导引 章节 描述 简介 介绍以数据为中心的AI测评(DataCLUE)的背景 任务描述 任务描述 实验结果
PPO is a very popular Reinforcement Learning algorithm at present.
PPO is a very popular Reinforcement Learning algorithm at present. OpenAI takes PPO as the current baseline algorithm. We use the PPO algorithm to train a policy to give the best action in any situation.
🍊 PAUSE (Positive and Annealed Unlabeled Sentence Embedding), accepted by EMNLP'2021 🌴
PAUSE: Positive and Annealed Unlabeled Sentence Embedding Sentence embedding refers to a set of effective and versatile techniques for converting raw
harmonic-percussive-residual separation algorithm wrapped as a VST3 plugin (iPlug2)
Harmonic-percussive-residual separation plug-in This work is a study on the plausibility of a sines-transients-noise decomposition inspired algorithm
SinglepassTextCluster, an TextCluster tools based on Singlepass cluster algorithm that use tfidf vector and doc2vec,which can be used for individual real-time corpus cluster task。基于single-pass算法思想的自动文本聚类小组件,内置tfidf和doc2vec两种文本向量方法,可自动输出聚类数目、类簇文档集合和簇类大小,用于自有实时数据的聚类任务。
项目的背景 SinglepassTextCluster, an TextCluster tool based on Singlepass cluster algorithm that use tfidf vector and doc2vec,which can be used for individ
A general-purpose, flexible, and easy-to-use simulator alongside an OpenAI Gym trading environment for MetaTrader 5 trading platform (Approved by OpenAI Gym)
gym-mtsim: OpenAI Gym - MetaTrader 5 Simulator MtSim is a simulator for the MetaTrader 5 trading platform alongside an OpenAI Gym environment for rein
RAMA: Rapid algorithm for multicut problem
RAMA: Rapid algorithm for multicut problem Solves multicut (correlation clustering) problems orders of magnitude faster than CPU based solvers without
Search algorithm implementations meant for teaching
Search-py A collection of search algorithms for teaching and experimenting. Non-adversarial Search There’s a heavy separation of concerns which leads
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
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 newly state-of-the-art recommendation models are implemented. QRec has a lightweight architecture and provides user-friendly interfaces. It can facilitate model implementation and evaluation.
Implementation of fast algorithms for Maximum Spanning Tree (MST) parsing that includes fast ArcMax+Reweighting+Tarjan algorithm for single-root dependency parsing.
Fast MST Algorithm Implementation of fast algorithms for (Maximum Spanning Tree) MST parsing that includes fast ArcMax+Reweighting+Tarjan algorithm fo
This project is an implementation of a simple K-means algorithm
Simple-Kmeans-Clustering-Algorithm Abstract K-means is a centroid-based algorithm, or a distance-based algorithm, where we calculate the distances to
A simple machine learning package to cluster keywords in higher-level groups.
Simple Keyword Clusterer A simple machine learning package to cluster keywords in higher-level groups. Example: "Senior Frontend Engineer" -- "Fronte
Sorting Algorithm Visualiser using pygame
SortingVisualiser Sorting Algorithm Visualiser using pygame Features Visualisation of some traditional sorting algorithms like quicksort and bubblesor
A custom prime algorithm, implementation, and performance code & review
Colander A custom prime algorithm, implementation, and performance code & review Pseudocode Algorithm 1. given a number of primes to find, the followi
Re-implementation of the Noise Contrastive Estimation algorithm for pyTorch, following "Noise-contrastive estimation: A new estimation principle for unnormalized statistical models." (Gutmann and Hyvarinen, AISTATS 2010)
Noise Contrastive Estimation for pyTorch Overview This repository contains a re-implementation of the Noise Contrastive Estimation algorithm, implemen
Graph-based community clustering approach to extract protein domains from a predicted aligned error matrix
Using a predicted aligned error matrix corresponding to an AlphaFold2 model , returns a series of lists of residue indices, where each list corresponds to a set of residues clustering together into a pseudo-rigid domain.
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized
Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+
Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+
Bayesian algorithm execution (BAX)
Bayesian Algorithm Execution (BAX) Code for the paper: Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mut
[CVPR2021] Domain Consensus Clustering for Universal Domain Adaptation
[CVPR2021] Domain Consensus Clustering for Universal Domain Adaptation [Paper] Prerequisites To install requirements: pip install -r requirements.txt
Code for the Population-Based Bandits Algorithm, presented at NeurIPS 2020.
Population-Based Bandits (PB2) Code for the Population-Based Bandits (PB2) Algorithm, from the paper Provably Efficient Online Hyperparameter Optimiza
DenseClus is a Python module for clustering mixed type data using UMAP and HDBSCAN
DenseClus is a Python module for clustering mixed type data using UMAP and HDBSCAN. Allowing for both categorical and numerical data, DenseClus makes it possible to incorporate all features in clustering.
Ceres is a combine harvester designed to harvest plots for Chia blockchain and its forks using proof-of-space-and-time(PoST) consensus algorithm.
Ceres Combine-Harvester Ceres is a combine harvester designed to harvest plots for Chia blockchain and its forks using proof-of-space-and-time(PoST) c
Code for the paper "JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design"
JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design This repository contains code for the paper: JA
This is the code for CVPR 2021 oral paper: Jigsaw Clustering for Unsupervised Visual Representation Learning
JigsawClustering Jigsaw Clustering for Unsupervised Visual Representation Learning Pengguang Chen, Shu Liu, Jiaya Jia Introduction This project provid
Fedlearn algorithm toolkit for researchers
Fedlearn algorithm toolkit for researchers
Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps
Proximal Backpropagation Proximal Backpropagation (ProxProp) is a neural network training algorithm that takes implicit instead of explicit gradient s
This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper
Deep Continuous Clustering Introduction This is a Pytorch implementation of the DCC algorithms presented in the following paper (paper): Sohil Atul Sh
Implements pytorch code for the Accelerated SGD algorithm.
AccSGD This is the code associated with Accelerated SGD algorithm used in the paper On the insufficiency of existing momentum schemes for Stochastic O
An all-in-one application to visualize multiple different local path planning algorithms
Table of Contents Table of Contents Local Planner Visualization Project (LPVP) Features Installation/Usage Local Planners Probabilistic Roadmap (PRM)
Fedlearn支持前沿算法研发的Python工具库 | Fedlearn algorithm toolkit for researchers
FedLearn-algo Installation Development Environment Checklist python3 (3.6 or 3.7) is required. To configure and check the development environment is c
Pytorch implementation of the DeepDream computer vision algorithm
deep-dream-in-pytorch Pytorch (https://github.com/pytorch/pytorch) implementation of the deep dream (https://en.wikipedia.org/wiki/DeepDream) computer
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte
This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch
This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment to test the algorithm
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A
PyTorch implementation of our Adam-NSCL algorithm from our CVPR2021 (oral) paper "Training Networks in Null Space for Continual Learning"
Adam-NSCL This is a PyTorch implementation of Adam-NSCL algorithm for continual learning from our CVPR2021 (oral) paper: Title: Training Networks in N
Решения, подсказки, тесты и утилиты для тренировки по алгоритмам от Яндекса.
Решения и подсказки к тренировке по алгоритмам от Яндекса Что есть внутри Решения с подсказками и комментариями; рекомендую сначала смотреть md файл п
An implementation of ordered dithering algorithm in python as multimedia course project
One way of minimizing the size of an image is to simply reduce the number of bits you use to represent each pixel.
Greedy Algorithm-Problem Solving
MAX-MIN-Hackrrank-Python-Solution Greedy Algorithm-Problem Solving You will be given a list of integers, , and a single integer . You must create an a
A minimal implementation of the IQRM interference flagging algorithm for radio pulsar and transient searches
A minimal implementation of the IQRM interference flagging algorithm for radio pulsar and transient searches. This module only provides the algorithm that infers a channel mask from some spectral statistic that measures the level of RFI contamination in a time-frequency data block. It should be useful as a reference implementation to developers who wish to integrate IQRM into an existing pipeline / search code.
Artificial Intelligence search algorithm base on Pacman
Pacman Search Artificial Intelligence search algorithm base on Pacman Source The Pacman Projects by the University of California, Berkeley. Layouts Di
GreenDoge is a modern community-centric green cryptocurrency based on a proof-of-space-and-time consensus algorithm.
GreenDoge Blockchain Download GreenDoge blockchain GreenDoge is a modern community-centric green cryptocurrency based on a proof-of-space-and-time con
An algorithm that handles large-scale aerial photo co-registration, based on SURF, RANSAC and PyTorch autograd.
An algorithm that handles large-scale aerial photo co-registration, based on SURF, RANSAC and PyTorch autograd.
An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)
AlphaZero-Gomoku This is an implementation of the AlphaZero algorithm for playing the simple board game Gomoku (also called Gobang or Five in a Row) f
Semantic Scholar's Author Disambiguation Algorithm & Evaluation Suite
S2AND This repository provides access to the S2AND dataset and S2AND reference model described in the paper S2AND: A Benchmark and Evaluation System f
Author's PyTorch implementation of Randomized Ensembled Double Q-Learning (REDQ) algorithm.
REDQ source code Author's PyTorch implementation of Randomized Ensembled Double Q-Learning (REDQ) algorithm. Paper link: https://arxiv.org/abs/2101.05
DI-HPC is an acceleration operator component for general algorithm modules in reinforcement learning algorithms
DI-HPC: Decision Intelligence - High Performance Computation DI-HPC is an acceleration operator component for general algorithm modules in reinforceme
Official repository for the paper "Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks"
Easy-To-Hard The official repository for the paper "Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks". Gett