This project demonstrates efficient weighted random sampling - a technique for selecting items from a collection where each item has a different probability of being chosen based on its assigned ...

The ignition point generated when a probability map is provided is not what is expected. Suppose you have three cells with probabilities [0.1, 0.5, 0.9]. Weighted sampling: Cell 1: 0.1 / (0.1+0.5+0.9) ...

This article describes a new Monte Carlo algorithm, dynamically weighted importance sampling (DWIS), for simulation and optimization. In DWIS, the state of the Markov chain is augmented to a ...

Abstract: Sampling random walks is a crucial component of many graph algorithms that perform graph embedding, link prediction, and other tasks. The effectiveness of these stochastic algorithms coupled ...

Abstract: 3D model feature extraction is a key step for geometric content based 3D model retrieval. A 3D model is usually expressed by patches and it has large amount of data. Pseudo-random sequential ...