Symbolic Learning in Python and Julia
Graph-Native Infrastructure for Context and Accountable AI Systems
白箱AGI架构探索:元认知(自我认知循环)、持续学习(知识飞轮)、世界模型(条件空间+语义时空图)、自我改进(自举纪律)、零LLM白箱管线与可审计信任护栏。
Make your agents talk human. ADHD-friendly output styles for Claude Code, Codex, and others. So you can pay attention, not tokens.
Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
AI on the way. An auto deep learning pipe dream. An RDBMS approach to deep learning. Declarative, explainable, scalable, optimizable, easy to deploy, all that good stuff.
Time Series Feature Extraction Library (TSFEL): 60+ statistical, temporal, spectral and fractal features for time series classification, regression and signal processing in Python
Shapley Values and Shapley Interactions for Machine Learning
👋 Xplique is a Neural Networks Explainability Toolbox
A cautious, explainable AI text detector for local workflows and coding agents. Need production detection in your app? Try the Lynote AI Detector API → lynote.ai/ai-detector-api
Evidence-grounded financial risk analysis from corporate filings, combining constrained LLM interpretation, deterministic analytics, versioned rules, and auditable evidence trails.
AI-powered Labour Law Violation Detection System using Weak Supervision, BiLSTM, Graph Neural Networks (GNN), and Explainable AI to identify labour law violations.
AI-powered fake news detection system with multiple ML models and explainability.