gradient-free-optimization

Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.

Lightweight optimization with local, global, population-based and sequential techniques across mixed search spaces

[JMLR (CCF-A)] PyPop7: A Pure-PYthon LibrarY for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* algorithm variants. In the near future, we will add Learning-Based Optimizers as its extensions. [https://jmlr.org/papers/v25/23-0386.html]

Gradient-free optimization method for the multidimensional arrays and discretized multivariate functions based on the tensor train (TT) format.

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.

Training non-differentiable networks via optimal transport.

A python package for consensus-based optimization

Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.

SwarmLoss: a PyTorch loss that trains through non-convex and non-differentiable objectives by fusing particle-swarm optimisation with gradient-based optimisers like Adam.

Modular optimization library for PyTorch (work-in-progress).

Markov Chain Monte Carlo binary network optimization

Deep Neural Network Optimization Platform with Gradient-based, Gradient-Free Algorithms

🥭 MANGO: Maximization of neural Activation via Non-Gradient Optimization

A curated collection of evolution strategies and zeroth-order optimization for large language models.

EvoRBF: A Nature-inspired Algorithmic Framework for Evolving Radial Basis Function Networks

Standardized test-functions for optimization algorithms and machine-learning

Blockwise Direct Search (MATLAB version)

Surrogate-based 0-th Order Global Optimization for black-box problems.

Gradient free reinforcement learning for PyTorch