A research toolkit for particle swarm optimization in Python
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Updated
Aug 6, 2024 - Python
A research toolkit for particle swarm optimization in Python
Portfolio optimization and back-testing.
Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.
A Genetic Algorithm Framework in Python (not for production level)
Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.
The official implementation of MARS: Unleashing the Power of Variance Reduction for Training Large Models
🎯 A comprehensive gradient-free optimization framework written in Python
Python-MIP: collection of Python tools for the modeling and solution of Mixed-Integer Linear programs
This repository implements several swarm optimization algorithms and visualizes them. Implemented algorithms: Particle Swarm Optimization (PSO), Firefly Algorithm (FA), Cuckoo Search (CS), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA)
Use PyTorch Models with CasADi for data-driven optimization or learning-based optimal control. Supports Acados.
Visualize Tensorflow's optimizers.
种群算法复现(swarm-algorithm),包括乌鸦搜��(Crow Search Algorithm, CSA)、樽海鞘群算法(Salp Swarm Algorithm, SSA)、缎蓝园丁鸟优化算法(Satin Bowerbird Optimizer, SBO)、麻雀搜索算法(Sparrow Search Algorithm, SSA)、 狼群搜索算法(2007WPS, 2013WPA)、正余弦优化算法(Sine Cosine Algorithm, CSA)、烟花算法(Fireworks Algorithm, FA)
多因子指数增强策略/多因子全流程实现
Sparse Optimisation Research Code
Python microframework for building nature-inspired algorithms. Official docs: https://niapy.org
Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"
zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
[JMLR (CCF-A)] PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* variants (including evolutionary algorithms, swarm-based randomized optimizers, pattern search, and random search). [https://jmlr.org/papers/v25/23-0386.html] (Its Planned Extensions: PyCoPop7, PyNoPop7, PyDPop77, and PyMePop7)
A toolkit for testing control and planning algorithm for car racing.
Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation preconditioner and more)
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