🔥 An autonomous AI agent that runs your deep learning experiments 24/7 while you sleep. Zero-cost monitoring, Leader-Worker architecture, constant-size memory.
AutoOED: Automated Optimal Experimental Design Platform
A GUI-forward Python framework for automating experimental setups.
Autonomous ML research on rental GPUs — LLM-driven hypothesis generation and fleet orchestration on RunPod
InfiEpisteme 📜 — Talk to Claude Code, get a research paper. 19 Markdown skills orchestrate the full pipeline: literature survey → ideation → experiments → writing → cross-model review. No framework, no lock-in — pure .md skills runnable by any LLM agent.
TraceOS standardizes AI experiments into reproducible, searchable, and comparable assets. One command runs experiments, generates reports, and produces structured analysis: capability vectors, failure taxonomy, and recommendations. Every run is tracked, traceable, and comparable. Built on ABC-130K (amazon-far/abc). Apache 2.0.
The ‘whisper_chunk_transcribe’ repository offers a Python script that utilizes OpenAI’s Whisper model to transcribe audio files in segments, enhancing accuracy and efficiency for lengthy recordings. It supports various audio formats and allows customization of chunk duration and overlap settings to optimize performance.
Search Google Scholar, enrich papers with OpenAlex, and build structured literature reviews locally.
Dynamic coding for Starlink measurement analysis and experiment automation
ENVI Classic 5.6 MCP and Codex skills for auditable remote-sensing lab automation and DOCX/PDF report generation.
A framework for the comparative training and evaluation of statistical and deep learning models for multi-feature categorical sequence modeling, utilizing feature fusion and automated with MLflow and Optuna integration.
Autonomous ML research loops for Claude Code with mechanical anti-fabrication guards.
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