Python Statistical-methods Resources

ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).

REMIX: Rule Extraction Methods for Interactive eXplainability This repository contains a variety of tools and methods for extracting interpretable rul

Doctoral dissertation of Zheng Zhao This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression pro

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

Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv

direpack: a Python 3 library for state-of-the-art statistical dimension reduction techniques This package delivers a scikit-learn compatible Python 3

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. 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

Code for the paper "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy" (arXiv:1611.04488; published at ICLR 2017), by Douga

MONEYBALL - ChatBot Module: 4006CEM, Class: B, Group: 5 Contributors: Jonas Djondo Roshan Kc Cole Samson Daniel Rodrigues Ihteshaam Naseer Kind remind

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) Important Notes NMSLIB is generic but fast, see the results of ANN benchmarks. A standalone implementation of our fa

tree-SNE t-SNE and hierarchical clustering are popular methods of exploratory data analysis, particularly in biology. Building on recent advances in s

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

vartests is a Python library to perform some statistic tests to evaluate Value at Risk (VaR) Models, such as: T-test: verify if mean of distribution i

roboticArmVisualizer Python GUI application to create custom linkages and adjust joint angles. In the future, I plan to add 2d inverse kinematics solv

Pyfunctools Pyfunctools is a module that provides functions, methods and classes that help in the creation of projects in python, bringing functional

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

Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic

Convoys is a simple library that fits a few statistical model useful for modeling time-lagged conversions. There is a lot more info if you head over to the documentation. You can also take a look at this blog post about Convoys.

m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code

A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Large Scale Learning on Non-Homophilous Graphs: New Benchmark

Venom Collection Of Discord Hacking Tools / Fun Stuff / Exploits That Is Completely Made Using Python. Report Bug · Request Feature Contributing Well,

AI-UPV at IberLEF-2021 DETOXIS task: Toxicity Detection in Immigration-Related Web News Comments Using Transformers and Statistical Models Description

Grounding Representation Similarity with Statistical Testing This repo contains code to replicate the results in our paper, which evaluates representa

pyLiDAR-SLAM This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods, which can easily be evaluated

Differentiable SVD Introduction This repository contains: The official Pytorch implementation of ICCV21 paper Why Approximate Matrix Square Root Outpe

Shape As Points (SAP) Paper | Project Page | Short Video (6 min) | Long Video (12 min) This repository contains the implementation of the paper: Shape

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 This is my Diploma Thesis ¨Road Crack Detection Using Deep Learning Methods¨ under the supervision of

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 ⚖️ The library of Natural Language Processing for Brazilian legal lang

Generalized Shape Metrics on Neural Representations In neuroscience and in deep learning, quantifying the (dis)similarity of neural representations ac

Git repositoty of the manuscript entitled Statistical quantification of confounding bias in predictive modelling by Tamas Spisak The manuscript descri

DAGSurv Survival analysis (SA) is a well-known statistical technique for the study of temporal events. In SA, time-to-an-event data is modeled using a

deprecat Decorator Python @deprecat decorator to deprecate old python classes, functions or methods. Installation pip install deprecat Usage To use th

A Comprehensive Study on Learning-Based PE Malware Family Classification Methods Datasets Because of copyright issues, both the MalwareBazaar dataset

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Large Scale Learning on Non-Homophilous Graphs: New Benchmark

Second-order Convergence Properties of Random Search Methods This repository the paper "On the Second-order Convergence Properties of Random Search Me

signed-area-causal-inference This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled

mlr3spatiotempcv Package website: release | dev Spatiotemporal resampling methods for mlr3. This package extends the mlr3 package framework with spati

Predicting 10-Year Treasury Yields Intitially, I wanted to see if the volatility in the stock market, represented by the VIX index (data source), had

Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods This repository is the official implementation of Seohong Park, Jaeky

Numerical methods Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary

StatisticalDistributions statDistros statDistros is a Python library for dealing with various statistical distributions. Now it provides various stati

Uncertainty Baselines The goal of Uncertainty Baselines is to provide a template for researchers to build on. The baselines can be a starting point fo

JumpDetectR Name of QuantLet : JumpDetectR Published in : 'To be published as "Jump dynamics in high frequency crypto markets"' Description : 'Scala

Continual Reinforcement Learning This repository provides a simple way to run continual reinforcement learning experiments in PyTorch, including evalu

🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.

PyTransKit Python Transport Based Signal Processing Toolkit Website and documentation: https://pytranskit.readthedocs.io/ Installation The library cou

SSSNET SSSNET: Semi-Supervised Signed Network Clustering For details, please read our paper. Environment Setup Overview The project has been tested on

Statistical Analysis 📈 This repository focuses on statistical analysis and the exploration used on various data sets for personal and professional pr

MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th

MMSceneGraph Introduction MMSceneneGraph is an open source code hub for scene graph generation as well as supporting downstream tasks based on the sce

Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment

Sci - cpy README is a stub. Do expand it. Objective This repository is meant to be a ready reference for scientific computation methods. Do ⭐ it if yo

Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.

geoopt Manifold aware pytorch.optim. Unofficial implementation for “Riemannian Adaptive Optimization Methods” ICLR2019 and more. Installation Make sur

GAN stability This repository contains the experiments in the supplementary material for the paper Which Training Methods for GANs do actually Converg

Graphlevel-SSL Overview Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Dataset). It is unified framework to co

Deep-Leafsnap Convolutional Neural Networks have become largely popular in image tasks such as image classification recently largely due to to Krizhev

The project is investigating methods to extract human-marked data from document forms such as surveys and tests. They can read questions, multiple-choice exam papers, and grade.

Factoral-Methods-using-two-different-method Here, I am finding the factorial of a number by using two different method. The first method is by using f

Three-different-method-for-list-reversion Here, I have discuss the three methods of list reversion. The three methods are built-in method, slicing met

mailcat The only cat who can find existing email addresses by nickname. Usage First install requirements: pip3 install -r requirements.txt Then just

solar-system Simulation of the solar system using various nummerical methods Download the repo Make shure matplotlib, scipy etc. are installed execute

Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.

Case studies with Bayesian methods

Cockpit: A Practical Debugging Tool for Training Deep Neural Networks

Noise Contrastive Estimation for pyTorch Overview This repository contains a re-implementation of the Noise Contrastive Estimation algorithm, implemen

Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Tested on many Common CNN Networks and Vision Transformers. ⭐ Includes smoo

AD penetration Testing Project By Ruben Enkaoua - GL4Di4T0R Based on the TCM PEH course (Heath Adams) Index 1 - Setting Up the Lab Intallation of a Wi

An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University

torch_DE_solver Combines power of torch, numerical methods and math overall to conquer and solve ALL {O,P}DEs There are three examples to provide a li

GAN stability This repository contains the experiments in the supplementary material for the paper Which Training Methods for GANs do actually Converg

beavis Pandas and Dask test helper methods with beautiful error messages. test helpers These test helper methods are meant to be used in test suites.

Knodle (Knowledge-supervised Deep Learning Framework) - a new framework for weak supervision with neural networks. It provides a modularization for se

NoW Evaluation This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard e

Exploration-Exploitation Dilemma Solving Methods Medium article for this repo - HERE In ths repo I implemented two techniques for tackling mentioned t

An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.

Password Mixin Mixin that adds some useful methods to ORM objects Compatible with Python 3.5 = 3.9 Install pip install password-mixin Setup first cre

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations This repo contains the Pytorch implementation of our paper: Revisit

Package pyVHR (short for Python framework for Virtual Heart Rate) is a comprehensive framework for studying methods of pulse rate estimation relying on remote photoplethysmography (rPPG)

Solve Volterra and Fredholm integral equations This Python package estimates Volterra and Fredholm integral equations using known techniques. Installa

Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. Not an official Google product. Me

Compositional Zero-Shot Learning This is the official PyTorch code of the CVPR 2021 works Learning Graph Embeddings for Compositional Zero-shot Learni

About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an

PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) an

Django-fakery An easy-to-use implementation of Creation Methods (aka Object Factory) for Django, backed by Faker. django_fakery will try to guess the

KAIST VIO dataset This is the dataset for testing the robustness of various VO/VIO methods You can download the whole dataset on KAIST VIO dataset Ind

End-to-End Coreference Resolution with Different Higher-Order Inference Methods This repository contains the implementation of the paper: Revealing th

Multi-Agent-Deep-Deterministic-Policy-Gradients A Pytorch implementation of the multi agent deep deterministic policy gradients(MADDPG) algorithm This

This tutorial's purpose is to introduce Pythonistas to methods for scaling their data science and machine learning work to larger datasets and larger models, using the tools and APIs they know and love from the PyData stack (such as numpy, pandas, and scikit-learn).

ReCo - Regional Contrast This repository contains the source code of ReCo and baselines from the paper, Bootstrapping Semantic Segmentation with Regio

StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both

...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on