Python Bayesian-optimization Resources

pycsminwel This is a locol minimization algorithm. Uses a quasi-Newton method with BFGS update of the estimated inverse hessian. It is robust against

MADGRAD Optimization Method A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization pip install madgrad Try it out! A best

Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a

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

Flyable - A python compiler for highly performant code Flyable is a Python compiler that generates efficient native code. It uses different techniques

Python HPC Optimizaciones incrementales de N-Body (all-pairs) con el fin de evaluar y comparar las prestaciones de los traductores de Python en el ámb

Curriculum Dropout Dropout is a very effective way of regularizing neural networks. Stochastically "dropping out" units with a certain probability dis

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

O S L O Open Source framework for Large-scale transformer Optimization What's New: December 21, 2021 Released OSLO 1.0. What is OSLO about? OSLO is a

PPOPT Python Parametric OPtimization Toolbox (PPOPT) is a software platform for solving and manipulating multiparametric programs in Python. This pack

CFMM Optimal Routing This repository contains the code needed to generate the figures used in the paper Optimal Routing for Constant Function Market M

pybnb A parallel branch-and-bound engine for Python. This software is copyright (c) by Gabriel A. Hackebeil (gabe.hacke

STORM Stochastic Tensor Optimization for Robot Motion - A GPU Robot Motion Toolkit [Install Instructions] [Paper] [Website] This package contains code

AdversarialTexture Adversarial Texture Optimization from RGB-D Scans (CVPR 2020). Scanning Data Download Please refer to data directory for details. B

Sklearn-genetic-opt scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms. This is meant to be an alternativ

The source code is temporariy removed, as we are solving potential copyright and license issues with GRANSO (http://www.timmitchell.com/software/GRANS

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

Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N

COSCO Framework COSCO is an AI based coupled-simulation and container orchestration framework for integrated Edge, Fog and Cloud Computing Environment

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

Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.

PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear

NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.

KIDA: Knowledge Inheritance in Data Aggregation This project releases our 1st place solution on NeurIPS2021 ML4CO Dual Task. Slide and model weights a

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

An implementation of the methods presented in Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.

[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects YouTube | arXiv Prerequisites Kaolin is available here:

geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins

This folder contains the code for 'Scalable Variational Approaches for Bayesian Causal Discovery'. Installation To install, use conda with conda env c

Pretrained Cost Model for Distributed Constraint Optimization Problems Requirements PyTorch 1.9.0 PyTorch Geometric 1.7.1 Directory structure baseline

Bayesian Deep Learning for Manufacturing 2.0 (dlmfg) Object Shape Error Response (OSER) Digital Lifecycle Management - In Process Quality Improvement

geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins

Graph Posterior Network This is the official code repository to the paper Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classifica

FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.

FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat

Bayesian Optimization over Permutation Spaces This repository contains the source code and the resources related to the paper "Bayesian Optimization o

PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural ne

slientruss3d : Python for stable truss analysis tool Desciption slientruss3d is a python package which can solve the resistances, internal forces and

Theseus A library for differentiable nonlinear optimization built on PyTorch to support constructing various problems in robotics and vision as end-to

Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation This is the implementation of the approach describ

Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner

DeepSpeed+Megatron trained the world's most powerful language model: MT-530B DeepSpeed is hiring, come join us! DeepSpeed is a deep learning optimizat

Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N

Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning This is the official repository of "Camera Distortion-

Adversarial Attacks on Graph Classification via Bayesian Optimisation @ NeurIPS 2021 This repository contains the official implementation of GRABNEL,

BEAR Overview This repository contains code associated with the preprint A generative nonparametric Bayesian model for whole genomes (2021), which pro

LMPBT Supplementary code for the Paper entitled ``Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models"

Permuton-induced Chinese Restaurant Process Note: Currently only the Matlab version is available, but a Python version will be available soon! This is

sNewton4PDEOpt The Python module implements a semismooth Newton method for solving finite-element discretizations of the strongly convex, linear ellip

Optimized Einsum Optimized Einsum: A tensor contraction order optimizer Optimized einsum can significantly reduce the overall execution time of einsum

Algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex)

8QueensGenetic A Python project for optimizing the 8 Queens Puzzle using the Genetic Algorithm implemented in PyGAD. The project uses the Kivy cross-p

Cutting Stock Problem Cutting Stock Problem (CSP) deals with planning the cutting of items (rods / sheets) from given stock items (which are usually o

NCVX NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning. Please check https://ncvx.org for detailed instruction

tsp-aco Ant Colony Optimization for Traveling Salesman Problem Dependencies Python 3.8 tqdm numpy matplotlib To run the solver run main.py from the p

Codebase for Amodal Segmentation through Out-of-Task andOut-of-Distribution Generalization with a Bayesian Model

Syne Tune This package provides state-of-the-art distributed hyperparameter optimizers (HPO) where trials can be evaluated with several backend option

Blitz - Bayesian Layers in Torch Zoo BLiTZ is a simple and extensible library to create Bayesian Neural Network Layers (based on whats proposed in Wei

DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation This repository is the implementation of DynaTune paper. This folder

g2o - General Graph Optimization Linux: Windows: g2o is an open-source C++ framework for optimizing graph-based nonlinear error functions. g2o has bee

Upgrade your print statements Loggers are like print() statements except they also include loads of other metadata: timestamp msg (same as print!) arg

Riskfolio-Lib Quantitative Strategic Asset Allocation, Easy for Everyone. Description Riskfolio-Lib is a library for making quantitative strategic ass

Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm

Sylvester normalizing flows for variational inference Pytorch implementation of Sylvester normalizing flows, based on our paper: Sylvester normalizing

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

BartPy Introduction BartPy is a pure python implementation of the Bayesian additive regressions trees model of Chipman et al [1]. Reasons to use BART

TransMorph: Transformer for Medical Image Registration keywords: Vision Transformer, Swin Transformer, convolutional neural networks, image registrati

mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.

DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari

zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl

early-ML Presentation General Machine Learning tutorials A Python step-by-step primer for Machine Learning and Optimization This github repository gat

By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated

What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of

Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie

DP-JOA Join optimization is the process of optimizing the joining, or combining, of two or more tables in a database. Here is a simple join optimizati

Racing Line Optimization with PSO This repository contains a racing line optimization algorithm in python that uses Particle Swarm Optimization. Requi

Visualization of numerical optimization algorithms

Bayesian Generative Adversarial Networks in Tensorflow This repository contains the Tensorflow implementation of the Bayesian GAN by Yunus Saatchi and

Kalman and Bayesian Filters in Python Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written

Prior-RObust Bayesian Optimization (PROBO) Introduction, TOC This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our

Coresets via Bilevel Optimization This is the reference implementation for "Coresets via Bilevel Optimization for Continual Learning and Streaming" ht

TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini

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

Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI

DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc

End of maintenance for GPyOpt Dear GPyOpt community! We would like to acknowledge the obvious. The core team of GPyOpt has moved on, and over the past

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

CVXPY The CVXPY documentation is at cvxpy.org. We are building a CVXPY community on Discord. Join the conversation! For issues and long-form discussio

Nevergrad - A gradient-free optimization platform nevergrad is a Python 3.6+ library. It can be installed with: pip install nevergrad More installati

blackbox: A Python module for parallel optimization of expensive black-box functions What is this? A minimalistic and easy-to-use Python module that e

Neural Architecture Search Powered by Swarm Intelligence 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle

Optuna: A hyperparameter optimization framework Website | Docs | Install Guide | Tutorial Optuna is an automatic hyperparameter optimization software

BBopt BBopt aims to provide the easiest hyperparameter optimization you'll ever do. Think of BBopt like Keras (back when Theano was still a thing) for

Dragonfly is an open source python library for scalable Bayesian optimisation. Bayesian optimisation is used for optimising black-box functions whose

Federated Learning with Non-IID Data This is an implementation of the following paper: Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vik

ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica

ProsePainter Create images by painting with words. ProsePainter combines direct digital painting with real-time guided machine-learning based image op

Multi-objective constrained optimization for energy applications via tree ensembles

Explaining Hyperparameter Optimization via PDPs This repository gives access to an implementation of the methods presented in the paper submission “Ex