165 Repositories
Python resampling-methods Libraries
Object-oriented programming (OOP) is a method of structuring a program by bundling related properties and behaviors into individual objects. In this tutorial, you’ll learn the basics of object-oriented programming in Python.
06_Python_Object_Class Introduction 👋 Objected oriented programming as a discipline has gained a universal following among developers. Python, an in-
Data types specify the different sizes and values that can be stored in the variable. For example, Python stores numbers, strings, and a list of values using different data types. Learn different types of Python data types along with their respective in-built functions and methods.
02_Python_Datatypes Introduction 👋 Data types specify the different sizes and values that can be stored in the variable. For example, Python stores n
Data stream analytics: Implement online learning methods to address concept drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams" accepted in IEEE GlobeCom 2021.
PWPAE-Concept-Drift-Detection-and-Adaptation This is the code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT
Evaluation and Benchmarking of Speech Super-resolution Methods
Speech Super-resolution Evaluation and Benchmarking What this repo do: A toolbox for the evaluation of speech super-resolution algorithms. Unify the e
Picasso: a methods for embedding points in 2D in a way that respects distances while fitting a user-specified shape.
Picasso Code to generate Picasso embeddings of any input matrix. Picasso maps the points of an input matrix to user-defined, n-dimensional shape coord
Best DDoS Attack Script Python3, Cyber Attack With 40 Methods
MXDDoS - DDoS Attack Script With 40 Methods (Code Lang - Python 3) Please Don't Attack '.gov' and '.ir' Websites :) Features And Methods 💣 Layer7 GET
PyTorch implementation for the paper Pseudo Numerical Methods for Diffusion Models on Manifolds
Pseudo Numerical Methods for Diffusion Models on Manifolds (PNDM) This repo is the official PyTorch implementation for the paper Pseudo Numerical Meth
Different steganography methods with examples and my own small image database
literally-the-most-useless-project [Different steganography methods with examples and my own small image database] This project currently contains thr
Crowd-Kit is a powerful Python library that implements commonly-used aggregation methods for crowdsourced annotation and offers the relevant metrics and datasets
Crowd-Kit: Computational Quality Control for Crowdsourcing Documentation Crowd-Kit is a powerful Python library that implements commonly-used aggregat
PacketPy is an open-source solution for stress testing network devices using different testing methods
PacketPy About PacketPy is an open-source solution for stress testing network devices using different testing methods. Currently, there are only two c
A python scripts that uses 3 different feature extraction methods such as SIFT, SURF and ORB to find a book in a video clip and project trailer of a movie based on that book, on to it.
A python scripts that uses 3 different feature extraction methods such as SIFT, SURF and ORB to find a book in a video clip and project trailer of a movie based on that book, on to it.
Our product DrLeaf which not only makes the work easier but also reduces the effort and expenditure of the farmer to identify the disease and its treatment methods.
Our product DrLeaf which not only makes the work easier but also reduces the effort and expenditure of the farmer to identify the disease and its treatment methods. We have to upload the image of an affected plant’s leaf through our website and our plant disease prediction model predicts and returns the disease name. And along with the disease name, we also provide the best suitable methods to cure the disease.
Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set
Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set This is the repository for the Deep Learning proje
Using NumPy to solve the equations of fluid mechanics together with Finite Differences, explicit time stepping and Chorin's Projection methods
Computational Fluid Dynamics in Python Using NumPy to solve the equations of fluid mechanics 🌊 🌊 🌊 together with Finite Differences, explicit time
Collections for the lasted paper about multi-view clustering methods (papers, codes)
Multi-View Clustering Papers Collections for the lasted paper about multi-view clustering methods (papers, codes). There also exists some repositories
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution Figure: Example visualization of the method and baseline as a
A mini-course offered to Undergrad chemistry students
The best way to use this material is by forking it by click the Fork button at the top, right corner. Then you will get your own copy to play with! Th
Self-Supervised Methods for Noise-Removal
SSMNR | Self-Supervised Methods for Noise Removal Image denoising is the task of removing noise from an image, which can be formulated as the task of
PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.
PEPit: Performance Estimation in Python This open source Python library provides a generic way to use PEP framework in Python. Performance estimation
Fully Adaptive Bayesian Algorithm for Data Analysis (FABADA) is a new approach of noise reduction methods. In this repository is shown the package developed for this new method based on \citepaper.
Fully Adaptive Bayesian Algorithm for Data Analysis FABADA FABADA is a novel non-parametric noise reduction technique which arise from the point of vi
Course on computational design, non-linear optimization, and dynamics of soft systems at UIUC.
Computational Design and Dynamics of Soft Systems · This is a repository that contains the source code for generating the lecture notes, handouts, exe
Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.
Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.
Fake News Detection Using Machine Learning Methods
Fake-News-Detection-Using-Machine-Learning-Methods Fake news is always a real and dangerous issue. However, with the presence and abundance of various
This repository collects 100 papers related to negative sampling methods.
Negative-Sampling-Paper This repository collects 100 papers related to negative sampling methods, covering multiple research fields such as Recommenda
Chess reinforcement learning by AlphaGo Zero methods.
About Chess reinforcement learning by AlphaGo Zero methods. This project is based on these main resources: DeepMind's Oct 19th publication: Mastering
YT-Spammer-Purge - Allows you easily scan for and delete scam comments using several methods
YouTube Spammer Purge What Is This? - Allows you to filter and search for spamme
Methods to get the probability of a changepoint in a time series.
Bayesian Changepoint Detection Methods to get the probability of a changepoint in a time series. Both online and offline methods are available. Read t
An example of time series augmentation methods with Keras
Time Series Augmentation This is a collection of time series data augmentation methods and an example use using Keras. News 2020/04/16: Repository Cre
A general and strong 3D object detection codebase that supports more methods, datasets and tools (debugging, recording and analysis).
ALLINONE-Det ALLINONE-Det is a general and strong 3D object detection codebase built on OpenPCDet, which supports more methods, datasets and tools (de
A new codebase for Group Activity Recognition. It contains codes for ICCV 2021 paper: Spatio-Temporal Dynamic Inference Network for Group Activity Recognition and some other methods.
Spatio-Temporal Dynamic Inference Network for Group Activity Recognition The source codes for ICCV2021 Paper: Spatio-Temporal Dynamic Inference Networ
Modeling cumulative cases of Covid-19 in the US during the Covid 19 Delta wave using Bayesian methods.
Introduction The goal of this analysis is to find a model that fits the observed cumulative cases of COVID-19 in the US, starting in Mid-July 2021 and
Inject your config variables into methods, so they are as close to usage as possible
Inject your config variables into methods, so they are as close to usage as possible
SimpleDepthEstimation - An unified codebase for NN-based monocular depth estimation methods
SimpleDepthEstimation Introduction This is an unified codebase for NN-based monocular depth estimation methods, the framework is based on detectron2 (
Awesome Graph Classification - A collection of important graph embedding, classification and representation learning papers with implementations.
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers
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
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
NumQMBasic - A mini-course offered to Undergrad physics students
The best way to use this material is by forking it by click the Fork button at the top, right corner. Then you will get your own copy to play with! Th
JudeasRx - graphical app for doing personalized causal medicine using the methods invented by Judea Pearl et al.
JudeasRX Instructions Read the references given in the Theory and Notation section below Fire up the Jupyter Notebook judeas-rx.ipynb The notebook dra
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
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
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
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
Flask-Diamond is a batteries-included Flask framework.
Flask-Diamond Flask-Diamond is a batteries-included Python Flask framework, sortof like Django but radically decomposable. Flask-Diamond offers some o
Denial Attacks by Various Methods
Denial Service Attack Denial Attacks by Various Methods IIIIIIIIIIIIIIIIIIII PPPPPPPPPPPPPPPPP VVVVVVVV VVVVVVVV I::
TeachMyAgent is a testbed platform for Automatic Curriculum Learning methods in Deep RL.
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL Paper Website Documentation TeachMyAgent is a testbed platform for Automatic Cu
Pytorch Lightning Implementation of SC-Depth Methods.
SC_Depth_pl: This is a pytorch lightning implementation of SC-Depth (V1, V2) for self-supervised learning of monocular depth from video. In the V1 (IJ
Machine learning algorithms for many-body quantum systems
NetKet NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and
Find exposed API keys based on RegEx and get exploitation methods for some of keys that are found
dora Features Blazing fast as we are using ripgrep in backend Exploit/PoC steps for many of the API key, allowing to write a good report for bug bount
A set of demo of deploying a Machine Learning Model in production using various methods
Machine Learning Model in Production This git is for those who have concern about serving your machine learning model to production. Overview The tuto
Fast methods to work with hydro- and topography data in pure Python.
PyFlwDir Intro PyFlwDir contains a series of methods to work with gridded DEM and flow direction datasets, which are key to many workflows in many ear
Package to provide translation methods for pyramid, and means to reload translations without stopping the application
Package to provide translation methods for pyramid, and means to reload translations without stopping the application
Computational Methods Course at UdeA. Forked and size reduced from:
Computational Methods for Physics & Astronomy Book version at: https://restrepo.github.io/ComputationalMethods by: Sebastian Bustamante 2014/2015 Dieg
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
PyDEns PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks. With PyDEns one can solve PD
Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks"
LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and
A library for researching neural networks compression and acceleration methods.
A library for researching neural networks compression and acceleration methods.
An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects different compression algorithms have.
ImageCompressionSimulation An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects o
Code accompanying "Adaptive Methods for Aggregated Domain Generalization"
Adaptive Methods for Aggregated Domain Generalization (AdaClust) Official Pytorch Implementation of Adaptive Methods for Aggregated Domain Generalizat
Code for the paper “The Peril of Popular Deep Learning Uncertainty Estimation Methods”
Uncertainty Estimation Methods Code for the paper “The Peril of Popular Deep Learning Uncertainty Estimation Methods” Reference If you use this code,
Evaluating saliency methods on artificial data with different background types
Evaluating saliency methods on artificial data with different background types This repository contains the relevant code for the MedNeurips 2021 subm
An implementation of the methods presented in Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.
An implementation of the methods presented in Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.
Tensorflow 2 implementations of the C-SimCLR and C-BYOL self-supervised visual representation methods from "Compressive Visual Representations" (NeurIPS 2021)
Compressive Visual Representations This repository contains the source code for our paper, Compressive Visual Representations. We developed informatio
[CVPR 2020] Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective
Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective [Arxiv] This is PyTorch implementation of th
Official PyTorch implementation of RIO
Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection Figure 1: Our proposed Resampling at image-level and obect-
Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks"
LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and
Lattice methods in TensorFlow
TensorFlow Lattice TensorFlow Lattice is a library that implements constrained and interpretable lattice based models. It is an implementation of Mono
Allows you to canibalize methods from classes effectively implementing trait-oriented programming
About This package enables code reuse in non-inheritance way from existing classes, effectively implementing traits-oriented programming pattern. Stor
Confidence Propagation Cluster aims to replace NMS-based methods as a better box fusion framework in 2D/3D Object detection
CP-Cluster Confidence Propagation Cluster aims to replace NMS-based methods as a better box fusion framework in 2D/3D Object detection, Instance Segme
Randomisation-based inference in Python based on data resampling and permutation.
Randomisation-based inference in Python based on data resampling and permutation.
A package with multiple bias correction methods for climatic variables, including the QM, DQM, QDM, UQM, and SDM methods
A package with multiple bias correction methods for climatic variables, including the QM, DQM, QDM, UQM, and SDM methods
Code for paper "Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs"
This is the codebase for the paper: Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs Directory Structur
FlowTorch is a PyTorch library for learning and sampling from complex probability distributions using a class of methods called Normalizing Flows
FlowTorch is a PyTorch library for learning and sampling from complex probability distributions using a class of methods called Normalizing Flows.
Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.
Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.
Code for paper "Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs"
This is the codebase for the paper: Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs Directory Structur
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods
ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).
Rule Extraction Methods for Interactive eXplainability
REMIX: Rule Extraction Methods for Interactive eXplainability This repository contains a variety of tools and methods for extracting interpretable rul
This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression problems
Doctoral dissertation of Zheng Zhao This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression pro
A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al.
pyUpSet A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al. Contents Purpose How to install How it work
Current state of supervised and unsupervised depth completion methods
Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv
A Python 3 package for state-of-the-art statistical dimension reduction methods
direpack: a Python 3 library for state-of-the-art statistical dimension reduction techniques This package delivers a scikit-learn compatible Python 3
Python package for missing-data imputation with deep learning
MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant
zeus is a Python implementation of the Ensemble Slice Sampling method.
zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl
A number of methods in order to perform Natural Language Processing on live data derived from Twitter
A number of methods in order to perform Natural Language Processing on live data derived from Twitter
Learning kernels to maximize the power of MMD tests
Code for the paper "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy" (arXiv:1611.04488; published at ICLR 2017), by Douga
Deep metric learning methods implemented in Chainer
Deep Metric Learning Implementation of several methods for deep metric learning in Chainer v4.2.0. Proxy-NCA: No Fuss Distance Metric Learning using P
Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.
Non-Metric Space Library (NMSLIB) Important Notes NMSLIB is generic but fast, see the results of ANN benchmarks. A standalone implementation of our fa
t-SNE and hierarchical clustering are popular methods of exploratory data analysis, particularly in biology.
tree-SNE t-SNE and hierarchical clustering are popular methods of exploratory data analysis, particularly in biology. Building on recent advances in s
Using some basic methods to show linkages and transformations of robotic arms
roboticArmVisualizer Python GUI application to create custom linkages and adjust joint angles. In the future, I plan to add 2d inverse kinematics solv
Pyfunctools is a module that provides functions, methods and classes that help in the creation of projects in python
Pyfunctools Pyfunctools is a module that provides functions, methods and classes that help in the creation of projects in python, bringing functional
MRI reconstruction (e.g., QSM) using deep learning methods
deepMRI: Deep learning methods for MRI Authors: Yang Gao, Hongfu Sun This repo is devloped based on Pytorch (1.8 or later) and matlab (R2019a or later
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.
[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Large Scale Learning on Non-Homophilous Graphs: New Benchmark
Collection Of Discord Hacking Tools / Fun Stuff / Exploits That Is Completely Made Using Python.
Venom Collection Of Discord Hacking Tools / Fun Stuff / Exploits That Is Completely Made Using Python. Report Bug · Request Feature Contributing Well,
This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods
pyLiDAR-SLAM This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods, which can easily be evaluated
A collection of differentiable SVD methods and also the official implementation of the ICCV21 paper "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?"
Differentiable SVD Introduction This repository contains: The official Pytorch implementation of ICCV21 paper Why Approximate Matrix Square Root Outpe
[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver
Shape As Points (SAP) Paper | Project Page | Short Video (6 min) | Long Video (12 min) This repository contains the implementation of the paper: Shape
Code repository for EMNLP 2021 paper 'Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods'
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods This is the code repository to accompany the EMNLP 2021 paper on ad
Road Crack Detection Using Deep Learning Methods
Road-Crack-Detection-Using-Deep-Learning-Methods This is my Diploma Thesis ¨Road Crack Detection Using Deep Learning Methods¨ under the supervision of
Svector (pronounced Swag-tor) provides extension methods to pyrsistent data structures
Svector Svector (pronounced Swag-tor) provides extension methods to pyrsistent data structures. Easily chain your methods confidently with tons of add
LegalNLP - Natural Language Processing Methods for the Brazilian Legal Language
LegalNLP - Natural Language Processing Methods for the Brazilian Legal Language ⚖️ The library of Natural Language Processing for Brazilian legal lang
Some methods for comparing network representations in deep learning and neuroscience.
Generalized Shape Metrics on Neural Representations In neuroscience and in deep learning, quantifying the (dis)similarity of neural representations ac