GitHub

Python implementation of the TurboQuant and QJL vector quantization algorithms.

turboquant-py implements the TurboQuant and QJL vector quantization algorithms from Google Research (ICLR 2026 / AISTATS 2026). It compresses high-dimensional floating-point vectors to 1-4 bits per ...
GitHub

Making a Class Schedule Using a Genetic Algorithm with Python

Making a class schedule is one of those NP hard problems. The problem can be solved using a heuristic search algorithm to find the optimal solution, but it only works for simple cases. For more ...
Frontiers

Random forest grid fault prediction based on genetic algorithm optimization

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...
IEEE

A General, Fast, and Robust Implementation of the Time-Optimal Path Parameterization Algorithm

Abstract: Finding the time-optimal parameterization of a given path subject to kinodynamic constraints is an essential component in many robotic theories and applications. The objective of this paper ...
IEEE

Research on Path Planning Algorithm Based on D* Search

Abstract: Path planning algorithms are current research hotspots. Heuristic algorithms that can solve dynamic environment problems are gradually becoming the mainstream research direction. The D* ...
Scientific Research Publishing

Multi-Strategy-Driven Salp Swarm Algorithm for Global Optimization ()

In response to the shortcomings of the Salp Swarm Algorithm (SSA) such as low convergence accuracy and slow convergence speed, a Multi-Strategy-Driven Salp Swarm Algorithm (MSD-SSA) was proposed.