738 Repositories
Python optimization-algorithms Libraries
A Lightweight Hyperparameter Optimization Tool 🚀
The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machine Learning Experiment (MLE) pipeline.
Implementation of Apriori algorithms via Python
Installing run bellow command for installing all packages pip install -r requirements.txt Data Put csv data under this directory "infrastructure/data
Tools for investing in Python
InvestOps Original repository on GitHub Original author is Magnus Erik Hvass Pedersen Introduction This is a Python package with simple and effective
OpenNeoMC:an Open-source Tool for Particle Transport Optimization that Combining OpenMC with NEORL
OpenNeoMC:an Open-source Tool for Particle Transport Optimization that Combining OpenMC with NEORL OpenMC is a community-developed Monte Carlo neutron
NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.
AMAZ3DSim AMAZ3DSim is a lightweight python-based 3D network multi-agent simulator. It uses a cell-based congestion model. It calculates risk, battery
A short non 100% Accurate Solar System in pygame
solar-system-pygame Controls UP/DOWN for Emulation Speed Control ESC for Pause/Unpause q to Quit c or ESC again to Continue LEFT CLICK to Add an orbit
Stochastic Gradient Trees implementation in Python
Stochastic Gradient Trees - Python Stochastic Gradient Trees1 by Henry Gouk, Bernhard Pfahringer, and Eibe Frank implementation in Python. Based on th
Federated_learning codes used for the the paper "Evaluation of Federated Learning Aggregation Algorithms" and "A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison"
Federated Distance (FedDist) This is the code accompanying the Percom2021 paper "A Federated Learning Aggregation Algorithm for Pervasive Computing: E
NAS-HPO-Bench-II is the first benchmark dataset for joint optimization of CNN and training HPs.
NAS-HPO-Bench-II API Overview NAS-HPO-Bench-II is the first benchmark dataset for joint optimization of CNN and training HPs. It helps a fair and low-
PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features
PyImpetus PyImpetus is a Markov Blanket based feature selection algorithm that selects a subset of features by considering their performance both indi
Code and datasets for the paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction"
KnowPrompt Code and datasets for our paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction" Requireme
A bare-bones Python library for quality diversity optimization.
pyribs Website Source PyPI Conda CI/CD Docs Docs Status Twitter pyribs.org GitHub docs.pyribs.org A bare-bones Python library for quality diversity op
Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale.
Model Search Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale. It aims to help researchers sp
Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python.
What is Retentioneering? Retentioneering is a Python framework and library to assist product analysts and marketing analysts as it makes it easier to
Data Structures and algorithms package implementation
Documentation Simple and Easy Package --This is package for enabling basic linear and non-linear data structures and algos-- Data Structures Array Sta
MBPO (paper: When to trust your model: Model-based policy optimization) in offline RL settings
offline-MBPO This repository contains the code of a version of model-based RL algorithm MBPO, which is modified to perform in offline RL settings Pape
Python Implementation of algorithms in Graph Mining, e.g., Recommendation, Collaborative Filtering, Community Detection, Spectral Clustering, Modularity Maximization, co-authorship networks.
Graph Mining Author: Jiayi Chen Time: April 2021 Implemented Algorithms: Network: Scrabing Data, Network Construbtion and Network Measurement (e.g., P
Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO)
V-MPO Simple code to demonstrate Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO) in Pyt
All algorithms implemented in Python for education
The Algorithms - Python All algorithms implemented in Python - for education Implementations are for learning purposes only. As they may be less effic
Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.
CTC Decoding Algorithms Update 2021: installable Python package Python implementation of some common Connectionist Temporal Classification (CTC) decod
A Python package implementing various HDRI / Radiance image processing algorithms.
Colour - HDRI A Python package implementing various HDRI / Radiance image processing algorithms. It is open source and freely available under the New
A Python package implementing various CFA (Colour Filter Array) demosaicing algorithms and related utilities.
Colour - Demosaicing A Python package implementing various CFA (Colour Filter Array) demosaicing algorithms and related utilities. It is open source a
This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,
labml.ai Deep Learning Paper Implementations This is a collection of simple PyTorch implementations of neural networks and related algorithms. These i
Recommendation algorithms for large graphs
Fast recommendation algorithms for large graphs based on link analysis. License: Apache Software License Author: Emmanouil (Manios) Krasanakis Depende
A library for optimization on Riemannian manifolds
TensorFlow RiemOpt A library for manifold-constrained optimization in TensorFlow. Installation To install the latest development version from GitHub:
Python Image Optimizer Script
Image-Optimizer Download and Install git clone https://github.com/stefankumpan/Image-Optimizer-Script.git cd Image-Optimizer-Script pip install -r req
PyTorch implementation of Constrained Policy Optimization
PyTorch implementation of Constrained Policy Optimization (CPO) This repository has a simple to understand and use implementation of CPO in PyTorch. A
FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
This repository contains the code accompanying the paper " FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation" Paper link: R
Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train format
ttopt Description Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train (TT) format and maximu
An index of recommendation algorithms that are based on Graph Neural Networks.
An index of recommendation algorithms that are based on Graph Neural Networks.
Kimimaro: Skeletonize Densely Labeled Images
Kimimaro: Skeletonize Densely Labeled Images # Produce SWC files from volumetric images. kimimaro forge labels.npy --progress # writes to ./kimimaro_o
Lale is a Python library for semi-automated data science.
Lale is a Python library for semi-automated data science. Lale makes it easy to automatically select algorithms and tune hyperparameters of pipelines that are compatible with scikit-learn, in a type-safe fashion.
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond
Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations.
BO-GP Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations. The BO-GP codes are developed using GPy and GPyOpt. The optimizer
ETMO: Evolutionary Transfer Multiobjective Optimization
ETMO: Evolutionary Transfer Multiobjective Optimization To promote the research on ETMO, benchmark problems are of great importance to ETMO algorithm
Solver for Large-Scale Rank-One Semidefinite Relaxations
STRIDE: spectrahedral proximal gradient descent along vertices A Solver for Large-Scale Rank-One Semidefinite Relaxations About STRIDE is designed for
Tindicators is a Python library to calculate the values of various technical indicators
Tindicators is a Python library to calculate the values of various technical indicators
A gui application to visualize various sorting algorithms using pure python.
Sorting Algorithm Visualizer A gui application to visualize various sorting algorithms using pure python. Language : Python 3 Libraries required Tkint
Cirq is a Python library for writing, manipulating, and optimizing quantum circuits and running them against quantum computers and simulators
Cirq is a Python library for writing, manipulating, and optimizing quantum circuits and running them against quantum computers and simulators. Install
Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
Nature-inspired algorithms are a very popular tool for solving optimization problems.
Nature-inspired algorithms are a very popular tool for solving optimization problems. Numerous variants of nature-inspired algorithms have been develo
A numpy-based implementation of RANSAC for fundamental matrix and homography estimation. The degeneracy updating and local optimization components are included and optional.
Description A numpy-based implementation of RANSAC for fundamental matrix and homography estimation. The degeneracy updating and local optimization co
CONetV2: Efficient Auto-Channel Size Optimization for CNNs
CONetV2: Efficient Auto-Channel Size Optimization for CNNs Exciting News! CONetV2: Efficient Auto-Channel Size Optimization for CNNs has been accepted
Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations
Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations Requirements The code is implemented in Python and requires
Deep Sea Treasure Environment for Multi-Objective Optimization Research
DeepSeaTreasure Environment Installation In order to get started with this environment, you can install it using the following command: python3 -m pip
A visualization tool made in Pygame for various pathfinding algorithms.
Pathfinding-Visualizer 🚀 A visualization tool made in Pygame for various pathfinding algorithms. Pathfinding is closely related to the shortest path
HyperaPy: An automatic hyperparameter optimization framework ⚡🚀
hyperpy HyperPy: An automatic hyperparameter optimization framework Description HyperPy: Library for automatic hyperparameter optimization. Build on t
Framework to build and train RL algorithms
RayLink RayLink is a RL framework used to build and train RL algorithms. RayLink was used to build a RL framework, and tested in a large-scale multi-a
🧬 Performant Evolutionary Algorithms For Python with Ray support
🧬 Performant Evolutionary Algorithms For Python with Ray support
Experiments for distributed optimization algorithms
Network-Distributed Algorithm Experiments -- This repository contains a set of optimization algorithms and objective functions, and all code needed to
MPI Interest Group on Algorithms on 1st semester 2021
MPI Algorithms Interest Group Introduction Lecturer: Steve Yan Location: TBA Time Schedule: TBA Semester: 1 Useful URLs Typora: https://typora.io Goog
Machine Learning Algorithms
Machine-Learning-Algorithms In this project, the dataset was created through a survey opened on Google forms. The purpose of the form is to find the p
This is an amazing game make using pygame.
This is an awesome balloon game. It is made in python using Pygame library. It is a project game while learning game development.
Leetcode solutions - All algorithms implemented in Python 3 (for education)
Leetcode solutions - All algorithms implemented in Python 3 (for education)
Deep learning algorithms for muon momentum estimation in the CMS Trigger System
Deep learning algorithms for muon momentum estimation in the CMS Trigger System The Compact Muon Solenoid (CMS) is a general-purpose detector at the L
OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.
OptaPy is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference Scheduling, Job Shop Scheduling, Bin Packing and many more planning problems.
Repositori untuk belajar pemrograman Python dalam bahasa Indonesia
Python Repositori ini berisi kumpulan dari berbagai macam contoh struktur data, algoritma dan komputasi matematika yang diimplementasikan dengan mengg
Azua - build AI algorithms to aid efficient decision-making with minimum data requirements.
Project Azua 0. Overview Many modern AI algorithms are known to be data-hungry, whereas human decision-making is much more efficient. The human can re
This repository is for adding codes of data structures and algorithms, leetCode, hackerrank etc solutions in different languages
DSA-Code-Snippet This repository is for adding codes of data structures and algorithms, leetCode, hackerrank etc solutions in different languages Cont
This repository is a compilation of important Data Structures and Algorithms based on Python.
Python DSA 🐍 This repository is a compilation of important Data Structures and Algorithms based on Python. Please make seperate folders for different
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
A topology optimization framework written in Taichi programming language, which is embedded in Python.
Taichi TopOpt (Under Active Development) Intro A topology optimization framework written in Taichi programming language, which is embedded in Python.
Fast batch image resizer and rotator for JPEG and PNG images.
imgp is a command line image resizer and rotator for JPEG and PNG images.
🧬 Training the car to do self-parking using a genetic algorithm
🧬 Training the car to do self-parking using a genetic algorithm
Reinforcement learning framework and algorithms implemented in PyTorch.
Reinforcement learning framework and algorithms implemented in PyTorch.
A framework for large scale recommendation algorithms.
A framework for large scale recommendation algorithms.
NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training
NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training
A Python Package for Portfolio Optimization using the Critical Line Algorithm
A Python Package for Portfolio Optimization using the Critical Line Algorithm
A Python Package for Portfolio Optimization using the Critical Line Algorithm
PyCLA A Python Package for Portfolio Optimization using the Critical Line Algorithm Getting started To use PyCLA, clone the repo and install the requi
OptNet: Differentiable Optimization as a Layer in Neural Networks
OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc
Riemannian Adaptive Optimization Methods with pytorch optim
geoopt Manifold aware pytorch.optim. Unofficial implementation for “Riemannian Adaptive Optimization Methods” ICLR2019 and more. Installation Make sur
ppo_pytorch_cpp - an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch
PPO Pytorch C++ This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment t
Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286
Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https
easyopt is a super simple yet super powerful optuna-based Hyperparameters Optimization Framework that requires no coding.
easyopt is a super simple yet super powerful optuna-based Hyperparameters Optimization Framework that requires no coding.
PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch
Advantage async actor-critic Algorithms (A3C) in PyTorch @inproceedings{mnih2016asynchronous, title={Asynchronous methods for deep reinforcement lea
PyTorch implementation of Deformable Convolution
PyTorch implementation of Deformable Convolution !!!Warning: There is some issues in this implementation and this repo is not maintained any more, ple
Implementation of algorithms for continuous control (DDPG and NAF).
DEPRECATION This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.
OptNet: Differentiable Optimization as a Layer in Neural Networks
OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc
Task-based end-to-end model learning in stochastic optimization
Task-based End-to-end Model Learning in Stochastic Optimization This repository is by Priya L. Donti, Brandon Amos, and J. Zico Kolter and contains th
Official PyTorch code of DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context Graph and Relation-based Optimization (ICCV 2021 Oral).
DeepPanoContext (DPC) [Project Page (with interactive results)][Paper] DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context G
Certifiable Outlier-Robust Geometric Perception
Certifiable Outlier-Robust Geometric Perception About This repository holds the implementation for certifiably solving outlier-robust geometric percep
Rafael Project- Classifying rockets to different types using data science algorithms.
Rocket-Classify Rafael Project- Classifying rockets to different types using data science algorithms. In this project we received data base with data
Entropy-controlled contexts in Python
Python module ordered ordered module is the opposite to random - it maintains order in the program. import random x = 5 def increase(): global x
PennyLane is a cross-platform Python library for differentiable programming of quantum computers.
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
GNPy: Optical Route Planning and DWDM Network Optimization
GNPy is an open-source, community-developed library for building route planning and optimization tools in real-world mesh optical networks
OptaPlanner wrappers for Python. Currently significantly slower than OptaPlanner in Java or Kotlin.
OptaPy is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference Scheduling, Job Shop Scheduling, Bin Packing and many more planning problems.
Extract and visualize information from Gurobi log files
GRBlogtools Extract information from Gurobi log files and generate pandas DataFrames or Excel worksheets for further processing. Also includes a wrapp
Automated Hyperparameter Optimization Competition
QQ浏览器2021AI算法大赛 - 自动超参数优化竞赛 ACM CIKM 2021 AnalyticCup 在信息流推荐业务场景中普遍存在模型或策略效果依赖于“超参数”的问题,而“超参数"的设定往往依赖人工经验调参,不仅效率低下维护成本高,而且难以实现更优效果。因此,本次赛题以超参数优化为主题,从真
In this Github repository I will share my freqtrade files with you. I want to help people with this repository who don't know Freqtrade so much yet.
My Freqtrade stuff In this Github repository I will share my freqtrade files with you. I want to help people with this repository who don't know Freqt
scrilla: A Financial Optimization Application
A python application that wraps around AlphaVantage, Quandl and IEX APIs, calculates financial statistics and optimizes portfolio allocations.
Solving a card game with three search algorithms: BFS, IDS, and A*
Search Algorithms Overview In this project, we want to solve a card game with three search algorithms. In this card game, we have to sort our cards by
Implementation of fast algorithms for Maximum Spanning Tree (MST) parsing that includes fast ArcMax+Reweighting+Tarjan algorithm for single-root dependency parsing.
Fast MST Algorithm Implementation of fast algorithms for (Maximum Spanning Tree) MST parsing that includes fast ArcMax+Reweighting+Tarjan algorithm fo
An efficient framework for reinforcement learning.
rl: An efficient framework for reinforcement learning Requirements Introduction PPO Test Requirements name version Python =3.7 numpy =1.19 torch =1
[ICCV 2021 Oral] NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
NerfingMVS Project Page | Paper | Video | Data NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo Yi Wei, Shaohui
Official implementation of the MM'21 paper Constrained Graphic Layout Generation via Latent Optimization
[MM'21] Constrained Graphic Layout Generation via Latent Optimization This repository provides the official code for the paper "Constrained Graphic La
ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks
Sign-Agnostic Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page This repository contains the implementation
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
CARLA - Counterfactual And Recourse Library CARLA is a python library to benchmark counterfactual explanation and recourse models. It comes out-of-the
Differentiable Factor Graph Optimization for Learning Smoothers @ IROS 2021
Differentiable Factor Graph Optimization for Learning Smoothers Overview Status Setup Datasets Training Evaluation Acknowledgements Overview Code rele
PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning.
neural-combinatorial-rl-pytorch PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning. I have implemented the basic