Python Approximate-bayesian-inference Resources

Memorizing Transformers - Pytorch Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memori

Optimum Transformers Accelerated NLP pipelines for fast inference 🚀 on CPU and GPU. Built with 🤗 Transformers, Optimum and ONNX runtime. Installatio

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

cloob-training Pretrained models There are two pretrained CLOOB models in this repo at the moment, a 16 epoch and a 32 epoch ViT-B/16 checkpoint train

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

SageMaker Studio Lab Sample Notebooks Available today in public preview. If you are looking for a no-cost compute environment to run Jupyter notebooks

NEW RELEASE How Nebullvm Works • Tutorials • Benchmarks • Installation • Get Started • Optimization Examples Discord | Website | LinkedIn | Twitter Ne

Data_Science_Interview_Questions Introduction 👋 Here are the answers to 120 Data Science Interview Questions The above answer some is modified based

💎A high level pipeline for face landmarks detection, supports training, evaluating, exporting, inference and 100+ data augmentations, compatible with torchvision and albumentations, can easily install with pip.

CaiT-TF (Going deeper with Image Transformers) This repository provides TensorFlow / Keras implementations of different CaiT [1] variants from Touvron

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

PMR computer tutorials on HMMs (2021-2022) This is a repository for computer tutorials of Probabilistic Modelling and Reasoning (2021/2022) - a Univer

Billion-Scale ANN http://big-ann-benchmarks.com/ Install The only prerequisite is Python (tested with 3.6) and Docker. Works with newer versions of Py

Hugging Face Optimum 🤗 Optimum is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to t

ConvNeXt-TF This repository provides TensorFlow / Keras implementations of different ConvNeXt [1] variants. It also provides the TensorFlow / Keras mo

Object Detection Object detection is a computer vision task for locating instances of predefined objects in images or videos. In this tutorial, you wi

ProbAI 2021 - Probabilistic Programming and Variational Inference Tutorial with Pryo Day 1 (June 14) Slides Notebook: students_PPLs_Intro Notebook: so

The Official Implementation of CLIB (Continual Learning for i-Blurry) Online Continual Learning on Class Incremental Blurry Task Configuration with An

Semi-automated OpenVINO benchmark_app with variable parameters. User can specify multiple options for any parameters in the benchmark_app and the progam runs the benchmark with all combinations of given options.

DeciWatch: A Simple Baseline for 10× Efficient 2D and 3D Pose Estimation This repo is the official implementation of "DeciWatch: A Simple Baseline for

Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation This is the implementaion of our paper: Bridging the

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

PyOpenVINO - An Experimental Python Implementation of OpenVINO Inference Engine (minimum-set) Description The PyOpenVINO is a spin-off product from my

ZEROGEN This repository contains the code for our paper “ZeroGen: Efficient Zero

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

Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical V

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

Over-the-Air Ensemble Inference with Model Privacy This repository contains simulations for our private ensemble inference method. Installation Instal

Graph Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, RDFlib, pySHACL, RAPIDS, NetworkX, iGraph, PyVis, pslpython, pyarrow, etc.

fast-Bart Reduction of BART model size by 3X, and boost in inference speed up to 3X BART implementation of the fastT5 library (https://github.com/Ki6a

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

Probabilistic U-Net + **Update** + An improved Model (the Hierarchical Probabilistic U-Net) + LIDC crops is now available. See below. Re-implementatio

Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b

Welcome! This readme will guide you through the use of the code in this reposito

GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online Debates Vibhor Agarwal, Sagar Joglekar, Anthony P. Young an

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

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

Approximate Multiplier by HEAM What's HEAM? HEAM is a general optimization method to generate high-efficiency approximate multipliers for specific app

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

Sequence-Labeling-Early-Exit Code for ACL 2021 paper: Accelerating BERT Inference for Sequence Labeling via Early-Exit Requirement: Please refer to re

Learning to propose objects This implements the learning and inference/proposal algorithm described in "Learning to Propose Objects, Krähenbühl and Ko

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).

An ongoing curated collection of awesome software, libraries, frameworks, talks & videos, best practices, learning tutorials and important practical resources about networking in cybersecurity

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

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

intro-to-causal-inference A introduction to causal inference using common tools from the python data stack Table of Contents Getting Started Install g

VIMuRe Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data. If you use this code please cite this article (preprint). De

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

TBSG: Tree-based Search Graph for Approximate Nearest Neighbor Search. TBSG is a graph-based algorithm for ANNS based on Cover Tree, which is also an

A Python package for simulating Active Inference agents in Markov Decision Process environments. Please see our companion preprint on arxiv for an ove

Accurate Phylogenetic Inference with a Symmetry-preserving Neural Network Model Claudia Solis-Lemus Shengwen Yang Leonardo Zepeda-Núñez This repositor

Fully Adaptive Bayesian Algorithm for Data Analysis FABADA FABADA is a novel non-parametric noise reduction technique which arise from the point of vi

Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup

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

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

GFNet-Pytorch (NeurIPS 2020) This repo contains the official code and pre-trained models for the glance and focus network (GFNet). Glance and Focus: a

NLP Best Practices In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive bus

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

CLIP-ONNX It is a simple library to speed up CLIP inference up to 3x (K80 GPU) Usage Install clip-onnx module and requirements first. Use this trick !

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

CV Backbones including GhostNet, TinyNet, TNT (Transformer in Transformer) developed by Huawei Noah's Ark Lab. GhostNet Code TinyNet Code TNT Code Pyr

Spatio-Temporal Variational GPs This repository is the official implementation of the methods in the publication: O. Hamelijnck, W.J. Wilkinson, N.A.

CorrProxies - Optimizing Machine Learning Inference Queries with Correlative Proxy Models

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.

Python wrapper class for OpenVINO Model Server. User can submit inference request to OVMS with just a few lines of code.

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

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

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

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval This repo provides personal implementation of paper Approximate Ne

ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme

English | 中文 OpenIVA OpenIVA is an end-to-end intelligent video analytics development toolkit based on different inference backends, designed to help

whylogs: A Data and Machine Learning Logging Standard whylogs is an open source standard for data and ML logging whylogs logging agent is the easiest

A minimalistic example of preparing a model for (synchronous) inference in production.

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

STOIC2021 Baseline Algorithm This codebase contains an example submission for the STOIC2021 COVID-19 AI Challenge. As a baseline algorithm, it impleme

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

BONITA-Python3 BONITA was originally written in Python 2 and tested with Python 2-compatible packages. This version of the packages ports BONITA to Py

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

v-diffusion-pytorch v objective diffusion inference code for PyTorch, by Katherine Crowson (@RiversHaveWings) and Chainbreakers AI (@jd_pressman). The

Here is some Python code that allows you to read in SVG files and approximate their paths using a Fourier series. The Fourier series can be animated and visualized, the function can be output as a two dimensional vector for Desmos and there is a method to output the coefficients as LaTeX code.

Table_Editor Convert Table data to approximate values with GUIs... usage - Import methods for extension Tables. Imported method supposed to have only

Bean Machine Overview Bean Machine is a probabilistic programming language for inference over statistical models written in the Python language using

fastshap: A fast, approximate shap kernel fastshap was designed to be: Fast Calculating shap values can take an extremely long time. fastshap utilizes

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

DeeBERT This is the code base for the paper DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference. Code in this repository is also available

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