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Monte-Carlo Geometry Processes for Solving PDEs

This repository showcases the differences between two Monte-Carlo geometry processes used to solve Partial Differential Equations (PDEs), with applications in generating 2D and 3D images.

📖 Overview

Monte-Carlo methods are widely used for solving complex PDEs due to their probabilistic approach and scalability to high-dimensional problems. This repository compares two distinct Monte-Carlo geometry techniques, highlighting their effectiveness, accuracy, and performance in 2D and 3D image generation tasks.

🎯 Objectives

  • Demonstrate the capabilities of each Monte-Carlo geometry process.
  • Analyze their differences in terms of computational efficiency and results.
  • Provide visual examples of 2D and 3D images generated using each method.

Reference

This Repository is based on https://www.cs.cmu.edu/~kmcrane/Projects/WalkOnStars/

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This repository shows the differences between two Monte-Carlo geometry processes to solve PDEs(Partial Differential Equations) that generate 2D and 3D images.

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