Pioneering statistical AI research through human-AI collaboration
Neural Networks for Missing Data Mechanism Detection
Revolutionary tool for distinguishing between MAR and MNAR mechanisms
Revealing true optimizer performance
Quantify how close optimizers actually get to global minima
GPU-Accelerated WENO Implementation
Modern PyTorch implementation of WENO schemes using convolution operations
Approximate Forgiveness Level in Neural Networks
Discovery that random pruning improves performance up to 70-80% sparsity
Statistics-Informed Neural Network Pruning
FANIM-based pruning with Wilcoxon statistical testing
Future dedicated platforms - currently in planning phase
Statistical tools for clinical research
Drag-and-drop clinical trial analysis with no coding required - upload data, configure analysis, download FDA-ready results
Pharmaceutical statistical analysis
No-code pharmaceutical statistical analysis with built-in regulatory compliance and automated FDA submission reports
Financial modeling and risk analysis
Point-and-click financial risk modeling and portfolio analysis - no programming, just upload data and get professional reports
Insurance analytics and risk modeling
Intuitive actuarial analysis interface - drag-and-drop claims data for reserving, pricing, and regulatory reporting
Free Foundation + Focused Interfaces
Unlike SAS with its bloated, expensive, one-size-fits-all approach, SGCX follows a modular philosophy:
PyRegression, PySurvival, PyMVNMLE
Open source. Forever.
Project Lacuna, AFL insights
Paid services.
No-code tools for specific industries
Drag, drop, go.
Want to code? Use our free libraries.
Want results without coding? Use our focused interfaces.
Need cutting-edge research? License our research products.