ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.

Run a Parallel Autonomous ML Research Organization on your OpenClaw instance.

P2PCLAW Research White Paper • Series II Francisco Angulo de Lafuente The Living Agent SOUL, Skills, and Evolutionary Memory in the P2PCLAW Cognitive Stack A Fusion with Karpathy’s autoresearch Architecture Building an Agent That Does Not Merely Navigate Knowledge — But Grows Version 2.0 — 2025

Research Agora: Claude Code skills, benchmarks & tools for ML researchers — paper writing, citation verification, experiment tracking, LaTeX automation

Quantum-inspired Echo State Network for multi-agent behavior analysis (MABe challenge)

Fork of Karpathy/arxiv-sanity: customized for autonomous AI-guided research on single GPU

Code for the paper "2Mamba2Furious: Linear in complexity, competitive in accuracy"

Automated Framework for Evaluating Chain-of-Thought Reasoning in LLMs.

Enhance research paper writing by organizing workflows, improving structure, and supporting self-review for clear, logical, and well-aligned content.

Hierarchical GNN for fake-news detection on NELA-GT-2022: multi-level graphs (word, sentence, article + metadata) + MLflow, baselines & explainability.

Hypothesis-first experiment tracking for agent-driven ML research, wired into Claude Code.

Benchmarking PEFT (LoRA vs adapters) for ECG segment classification using Wav2Vec2, HuBERT, and ECG-FM with full metric reporting and ablations.

Claude Code skill for autonomous ML research — from topic to LaTeX paper

Autonomous ML research agent skill (Agent Skills format). Designs experiments, deploys to Modal GPUs, tracks budget, iterates autonomously.

Parametric Sigmoid Linear Unit

Causal analysis framework using Double Machine Learning to quantitatively isolate the effect of model size on deep learning performance while controlling for confounders such as dataset size, training time, and hyperparameters.

This is a comprehensive analysis of 5 HPO algorithms- General Algorithms (GA), Particle Swarm Optimization (PSO), (DE), PyHopper HPO, Bayesian Optimization and HyperBand Optimization (BOHB),

This repository presents four Capstone projects developed as part of the "the AI Engineer" program

Julia implementation of ST-ProtoPNet for interpretable classification with support and trivial prototypes. Built on Flux.jl with custom losses, data prep tools, and 2D visualization.

A simplified three-phase research workflow for Claude Code: Discovery, Experiment, Paper