Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Trains cognitive agents to extract behavioral, temporal, and network patterns from complex interaction sequences.
Implements intrinsic motivation for AI agents using Schmidhuber's formal theory of creativity and compression progress.
Implements Fisher-Rao metrics and natural gradient optimization on statistical manifolds for advanced probabilistic modeling.
Implements Schmidhuber's curiosity-driven framework to provide AI agents with intrinsic motivation based on compression progress.
Facilitates 3-SAT reductions to colored subgraph isomorphism using non-backtracking geodesic gadgets and Möbius filtering.
Builds, trains, and validates high-fidelity psychological models from interaction patterns to simulate cognitive behavior and intellectual trajectories.
Implements advanced homological algebra frameworks including chain complexes, derived functors, and triangulated categories for BCI signal processing.
Extracts complex behavioral patterns and trains predictive learning agents from interaction sequences using multi-interpreter analysis.
Orchestrates spontaneous role assignment and hierarchical self-organization in multi-agent systems using topological and chemical organization principles.
Implements the Forward-Forward algorithm and local contrastive learning paradigms to train neural networks without backpropagation.
Simulates agentic artificial life and emergent behaviors within Turing-complete programmable environments using JAX.
Implements mathematical category theory abstractions to enable compositional learning and structured parameter transfer in AI models.
Implements high-performance agentic simulators using JAX for researching emergent behaviors and open-ended evolution.
Empowers Claude with expert-level statistical modeling, causal inference, and production-grade machine learning capabilities for enterprise data systems.
Generates high-quality AI images using leading models like FLUX, SDXL, and Ideogram through the fal.ai API.
Optimizes fal.ai AI model deployments for maximum speed, minimal latency, and reduced infrastructure costs.
Animates static images into high-quality cinematic videos using leading AI models like Kling, Luma, and Runway via the fal.ai API.
Generates rigorous, quantified probabilistic forecasts and scenario models for complex future events using Bayesian reasoning and superforecasting techniques.
Facilitates seamless video processing pipelines by integrating FFmpeg's robust I/O with OpenCV's powerful image manipulation capabilities.
Develops and optimizes Streamlit data applications for the Keboola platform using a robust validate-build-verify workflow.
Classifies and filters dependency graph paths using Möbius inversion to optimize proof structures and resolve circular logic.
Generates deterministic GF(3) colored identifiers for hierarchical spatial indexing and location-based clustering.
Generates group-theoretic structures and computational algebraic objects for the Plurigrid ASI ecosystem.
Transforms, edits, and enhances images using state-of-the-art fal.ai models including FLUX, ControlNet, and advanced upscalers.
Provides expert guidance and decision trees for selecting optimal fal.ai models based on quality, speed, and cost requirements.
Builds high-performance, GPU-accelerated video processing workflows using FFmpeg, OpenCV, and serverless infrastructure.
Generates professional cinematic videos from text descriptions using state-of-the-art models like Kling, Sora, and Runway.
Streamlines computer vision development with expert patterns for image processing, video analysis, and deep learning inference using OpenCV.
Provides comprehensive documentation and implementation patterns for integrating fal.ai's generative AI models via JavaScript, Python, and REST APIs.
Bridges Next.js applications with Modal.com for high-performance AI inference, GPU workloads, and heavy serverless compute.
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