Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
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Updated
Apr 27, 2025 - Python
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
[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)
ACL'2023: Multi-Task Pre-Training of Modular Prompt for Few-Shot Learning
Gradient-free optimization method for multivariable functions based on the low rank tensor train (TT) format and maximal-volume principle.
Gradient-free optimization method for the multidimensional arrays and discretized multivariate functions based on the tensor train (TT) format.
Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.
Deep Neural Network Optimization Platform with Gradient-based, Gradient-Free Algorithms
Markov Chain Monte Carlo binary network optimization
🥭 MANGO: Maximization of neural Activation via Non-Gradient Optimization
EvoRBF: A Nature-inspired Algorithmic Framework for Evolving Radial Basis Function Networks
Gradient free reinforcement learning for PyTorch
Modular optimization library for PyTorch.
A collection and visualization of single objective black-box functions for optimization benchmarking.
Implementation of smoothing-based optimization algorithms
Particle Swarm Optimiser
Black-box adversarial attacks on deep neural networks with tensor train (TT) decomposition and PROTES optimizer.
Sparse Perturbations for Improved Convergence in Stochastic Zeroth-Order Optimization
Exploring evolutionary protein fitness landscapes
Numerical optimization via mollifier smoothing
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