Python Bayesian-methods Resources

What is judgyprophet? judgyprophet is a Bayesian forecasting algorithm based on Prophet, that enables forecasting while using information known by the

KFAC-JAX - Second Order Optimization with Approximate Curvature in JAX Installation | Quickstart | Documentation | Examples | Citing KFAC-JAX KFAC-JAX

06_Python_Object_Class Introduction 👋 Objected oriented programming as a discipline has gained a universal following among developers. Python, an in-

02_Python_Datatypes Introduction 👋 Data types specify the different sizes and values that can be stored in the variable. For example, Python stores n

PWPAE-Concept-Drift-Detection-and-Adaptation This is the code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT

Description This repository contains code accompanying the following paper on the Make-It robotic flow chemistry platform developed by the Jensen Rese

Understanding Bayesian Classification This repository hosts the code to reproduce the results presented in the paper On Uncertainty, Tempering, and Da

Speech Super-resolution Evaluation and Benchmarking What this repo do: A toolbox for the evaluation of speech super-resolution algorithms. Unify the e

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

A variational Bayesian method for similarity learning in non-rigid image registration We provide the source code and the trained models used in the re

Improving evidential deep learning via multi task learning It is a repository of AAAI2022 paper, “Improving evidential deep learning via multi-task le

MXDDoS - DDoS Attack Script With 40 Methods (Code Lang - Python 3) Please Don't Attack '.gov' and '.ir' Websites :) Features And Methods 💣 Layer7 GET

Lightweight (Bayesian) Media Mix Model This is not an official Google product. L

Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical V

Pseudo Numerical Methods for Diffusion Models on Manifolds (PNDM) This repo is the official PyTorch implementation for the paper Pseudo Numerical Meth

B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search This is the offical implementation of the

literally-the-most-useless-project [Different steganography methods with examples and my own small image database] This project currently contains thr

Crowd-Kit: Computational Quality Control for Crowdsourcing Documentation Crowd-Kit is a powerful Python library that implements commonly-used aggregat

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.

Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern

Code Impementation for "Mold into a Graph: Efficient Bayesian Optimization over Mixed Spaces" This repo contains the implementation of GEBO algorithm.

Posterior temperature optimized Bayesian models for inverse problems in medical imaging Max-Heinrich Laves*, Malte Tölle*, Alexander Schlaefer, Sandy

Official Code for the Paper "Transformers Can Do Bayesian Inference" We train Transformers to do Bayesian Prediction on novel datasets for a large var

Overview Code and supplemental materials for Karduni et al., 2020 IEEE Vis. "A Bayesian cognition approach for belief updating of correlation judgemen

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 This is the repository for the Deep Learning proje

Python implementation of Weng-Lin Bayesian ranking, a better, license-free alternative to TrueSkill This is a port of the amazing openskill.js package

Computational Fluid Dynamics in Python Using NumPy to solve the equations of fluid mechanics 🌊 🌊 🌊 together with Finite Differences, explicit time

Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How TensorFlow implementation for Bayesian Modeling and Unce

This repository contains the scripts needed to generate the results from the paper Unity Propagation in Bayesian Networks Handling Inconsistency via U

Multi-View Clustering Papers Collections for the lasted paper about multi-view clustering methods (papers, codes). There also exists some repositories

Natural Posterior Network This repository provides the official implementation o

ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference, with the design goal of unifying the automation (of Monte Carlo simulations), user-friendliness (of the library), accessibility (from multiple programming environments), high-performance (at runtime), and scalability (across many parallel processors).

BayesPy Bayesian Inference Tools in Python Our goal is, given the discrete outcomes of events, estimate the distribution of categories. Using gradient

Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution Figure: Example visualization of the method and baseline as a

Efficient Online Bayesian Inference for Neural Bandits By Gerardo Durán-Martín, Aleyna Kara, and Kevin Murphy AISTATS 2022.

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

bayesian_testing is a small package for a quick evaluation of A/B (or A/B/C/...) tests using Bayesian approach.

Laplace Redux - Effortless Bayesian Deep Learning This repository contains the code to run the experiments for the paper Laplace Redux - Effortless Ba

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: 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 FABADA is a novel non-parametric noise reduction technique which arise from the point of vi

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.

Fake-News-Detection-Using-Machine-Learning-Methods Fake news is always a real and dangerous issue. However, with the presence and abundance of various

LQVAE-separation Code for "Unsupervised Source Separation via Bayesian inference in the latent domain" Paper Samples GT Compressed Separated Drums GT

Negative-Sampling-Paper This repository collects 100 papers related to negative sampling methods, covering multiple research fields such as Recommenda

Bayesian Modeling and Computation in Python Open access and Code This repository contains the open access version of the text and the code examples in

Bayesian Modelling in Python Welcome to "Bayesian Modelling in Python" - a tutorial for those interested in learning how to apply bayesian modelling t

About Chess reinforcement learning by AlphaGo Zero methods. This project is based on these main resources: DeepMind's Oct 19th publication: Mastering

YouTube Spammer Purge What Is This? - Allows you to filter and search for spamme

Bayesian Changepoint Detection Methods to get the probability of a changepoint in a time series. Both online and offline methods are available. Read t

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

ALLINONE-Det ALLINONE-Det is a general and strong 3D object detection codebase built on OpenPCDet, which supports more methods, datasets and tools (de

Spatio-Temporal Dynamic Inference Network for Group Activity Recognition The source codes for ICCV2021 Paper: Spatio-Temporal Dynamic Inference Networ

Think Bayes 2 by Allen B. Downey The HTML version of this book is here. Think Bayes is an introduction to Bayesian statistics using computational meth

Bayesian Neural Networks Pytorch implementations for the following approximate inference methods: Bayes by Backprop Bayes by Backprop + Local Reparame

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

SimpleDepthEstimation Introduction This is an unified codebase for NN-based monocular depth estimation methods, the framework is based on detectron2 (

Distributed Grid Descent: an algorithm for hyperparameter tuning guided by Bayesian inference, designed to run on multiple processes and potentially many machines with no central point of control.

A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers

Doing_bayesian_data_analysis This repository contains the Python version of the R programs described in the great book Doing bayesian data analysis (f

Pattern Recognition and Machine Learning (PRML) This project contains Jupyter notebooks of many the algorithms presented in Christopher Bishop's Patte

Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor

Saliency Methods 🔴 Now framework-agnostic! (Example core notebook) 🔴 🔗 For further explanation of the methods and more examples of the resulting ma

Statistical Rethinking with Python and PyMC3 This repository has been deprecated in favour of this one, please check that repository for updates, for

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

Statistical Rethinking: A Bayesian Course Using CmdStanPy and Plotnine Intro This repo contains the python/stan version of the Statistical Rethinking

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 Bric-a-Brac Collections of numerical techniques with Python and standard computational packages (Numpy, SciPy, Numba, Matplotlib ...). Diffe

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 Animação 3D da trajetória do Atrator de Lorenz, implementada em Python usando o método de Runge-Kutta de 4ª

pv_predict_unet-lstm Code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods." IEEE Transactions

Make Sure the dataset file "spamData.mat" is in the folder spam\src Environment: Python --version = 3.7 Third Party: numpy, matplotlib, math, scipy

Flask-Diamond Flask-Diamond is a batteries-included Python Flask framework, sortof like Django but radically decomposable. Flask-Diamond offers some o

Denial Service Attack Denial Attacks by Various Methods IIIIIIIIIIIIIIIIIIII PPPPPPPPPPPPPPPPP VVVVVVVV VVVVVVVV I::

Code for the paper: Adversarial Machine Learning: Bayesian Perspectives This repository contains code for reproducing the experiments in the ** Advers

TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL Paper Website Documentation TeachMyAgent is a testbed platform for Automatic Cu

Sampyl May 29, 2018: version 0.3 Sampyl is a package for sampling from probability distributions using MCMC methods. Similar to PyMC3 using theano to

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

NetKet NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and

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

Machine Learning Model in Production This git is for those who have concern about serving your machine learning model to production. Overview The tuto

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

Computational Methods for Physics & Astronomy Book version at: https://restrepo.github.io/ComputationalMethods by: Sebastian Bustamante 2014/2015 Dieg

dblmahmc Code to go with the paper "Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo" Requirements: https://github.com

PyDEns PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks. With PyDEns one can solve PD

Recursive Bayesian Networks This repository contains the code to reproduce the results from the NeurIPS 2021 paper Lieck R, Rohrmeier M (2021) Recursi

Bayesian Active Learning (BaaL) BaaL is an active learning library developed at ElementAI. This repository contains techniques and reusable components

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.

Mixquality_AL Final Term Project For Bayesian Machine Learning Lecture (XAI-623) Youtube Link The presentation is given in YoutubeLink Problem Formula

ImageCompressionSimulation An Image compression simulator that uses Source Extractor and Monte Carlo methods to examine the post compressive effects o

Adaptive Methods for Aggregated Domain Generalization (AdaClust) Official Pytorch Implementation of Adaptive Methods for Aggregated Domain Generalizat

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 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.