Volumetry: Multidimensional Probability Modeling
Research project focused on volumetric probability distribution modeling and visualization. Implements novel techniques for modeling complex multidimensional distributions using gaussian kernels, decision trees, and equipotential surface analysis.
Key Research Findings
Developed gaussian kernel extrusion techniques along random splines for complex distribution modeling
Implemented marginal density projection operations for multi-dimensional probability visualization
Created novel equipotential surface finding algorithms that uniformly sample solution spaces
Successfully modeled 3D logistic map distributions with entropy analysis
Demonstrated effectiveness of decision tree-based volumetric modeling approaches
Achieved both slicing and projection operations for multidimensional model analysis
Technical Details & Impact
Technologies Used
Research Status
Last updated: 2015
Research Impact
Contributed novel approaches to volumetric probability modeling and established techniques for equipotential surface analysis in multidimensional spaces
This research is part of ongoing open-source development. Contributions, discussions, and collaborations are welcome.