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 ...
The utilization of unmanned aerial vehicles (UAVs) has expanded significantly in recent years across both military and civilian sectors, positioning autonomous and safe flight as a critical research ...
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 ...
In today’s society, innovative technologies emerge endlessly, which greatly promote social progress and industrial transformation 1. Robot technology covers many fields such as mechanical engineering, ...
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 ...
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 ...
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* ...
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.
Solving the sliding puzzle using a basic AI algorithm. I had published this article on Medium in September of 2018. I have decided to create more content on my LinkedIn profile, thus rewriting this ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results