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)
The official implementation of MARS: Unleashing the Power of Variance Reduction for Training Large Models
Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.
🎯 A comprehensive gradient-free optimization framework written in Python
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.
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"
[JMLR (CCF-A)] PyPop7: A Pure-PYthon LibrarY for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* algorithm variants (from evolutionary computation, swarm intelligence, statistics, operations research, machine learning, mathematical optimization, meta-heuristics, auto-control etc.). [https://jmlr.org/papers/v25/23-0386.html]
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.
RAVEN is a flexible and multi-purpose probabilistic risk analysis, validation and uncertainty quantification, parameter optimization, model reduction and data knowledge-discovering framework.
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)
Algorithm for Cutting Stock Problem using Google OR-Tools. Link to the tool:
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