Minimum Degree Spanning Tree

This is part of the project Efficient identification of core and dead features in variability models

lightgbmのfeature-transform（特徴量の非線形化）をすることで、80,000を超える特徴量を線形回帰でも表現できることを示します

ONNLab is a framework and project for developing obfuscated neural networks, offering full control over training and inference, flexible architecture configuration, and seamless integration of custom components. Its core principle is systematic yet highly flexible design, enabling implementation of any architecture or training strategy.

A greedy outlier algorithm based on entropy. Implementation of He Z., Deng S., Xu X., Huang J.Z. (2006) A Fast Greedy Algorithm for Outlier Mining.

Software for the paper "dCSR: A Memory-Efficient Sparse Matrix Representation for Parallel Neural Network Inference"

An implementation of heightmap-based terrain generation algorithms.

Two-Stage Multithreshold Otsu method.

WiscKey is a highly SSD optimized key-value storage based on LevelDB.

Tao Ju's original C++ implementation, with CMake (compiles on Linux)

Python implementation of the PAMI 2012 paper "Measuring the Objectness of Image Windows" and the CVPR 2010 paper "What is an object ?"

Author's implementation of SoftCon: Simulation and Control of Soft-Bodied Animals with Biomimetic Actuators (SIGGRAPH Asia 2019 Technical Paper)