List of Algorithms Implemented in COINSTAC
This page lists the algorithms that are currently implemented as computations in COINSTAC. Each algorithm is designed to perform specific computational tasks related to data analysis, machine learning, or scientific research.
Table of Contents
Machine Learning Algorithms
- Brainage prediction using Support Vector Regression
- Differentially Private Support Vector Machines classifier
Decentralized Algorithms
- Decentralized Combat
- Decentralized Deep Artificial Neural Networks in COINSTAC (CPU capability only)
- Decentralized Deep Artificial Neural Networks in COINSTAC (GPU accelerated)
- Decentralized Dynamic Functional Connectivity (DDFNC) Pipeline
- Decentralized GICA
- Decentralized Linear Mixed Effects Model - Freesurfer
- Decentralized Linear Mixed Effects Model - VBM
- Decentralized Mancova
- Decentralized Multishot TSNE
- Decentralized Parallel Independent Component Analysis
- Decentralized Source Based Morphometry
- Decentralized Sparse Deep Artificial Neural Networks in COINSTAC
- Decentralized Sparse Deep Artificial Neural Networks in COINSTAC (GPU)
ENIGMA Algorithms
- ENIGMA PANSS DTI in COINSTAC
- ENIGMA PANSS T1 in COINSTAC
- ENIGMA SANS DTI in COINSTAC
- ENIGMA SANS T1 in COINSTAC
fMRI Preprocessing
- fMRI Preprocessing Pipeline for 12/32 channel data
- fMRI Preprocessing Pipeline with BIDS support
Other Algorithms
- HALFpipe test harness
- Plink Computation in COINSTAC
- Regression (Multishot) - CSV
- Regression (Multishot) - FreeSurfer Volumes
- Regression (Multishot) - VBM
- Regression - FreeSurfer Volumes
- Regression - VBM
- Ridge Regression (Singleshot) - FreeSurfer Volumes
- VBM Preprocessor