🏆 Agentic AI Innovation Challenge 2025 runs from Feb. 10th to March 25th, 2025
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Share Your Innovations in Causal Learning

Causal AI & Inference

Ready Tensor welcomes groundbreaking projects in causal inference and discovery. Share your innovations in causal modeling, counterfactual analysis, and intervention-based approaches with our global community of AI professionals.

Causal AI Innovation Graphic

Share Your Expertise

As AI systems mature, understanding causation becomes crucial for reliable decision-making. Ready Tensor provides a platform for practitioners to showcase their innovations in causal inference, discovery, and modeling. Share your work to advance the field of causality-aware machine learning.

Areas of Interest

Core Approaches:

  • Causal inference methods
  • Causal discovery algorithms
  • Counterfactual analysis
  • Treatment effect estimation
  • Causal feature selection
  • Intervention analysis

Advanced Techniques:

  • Structural causal models
  • Deep causal learning
  • Instrumental variables
  • Causal reinforcement learning
  • Time-varying causation
  • Cross-domain causality

Application Domains:

  • Healthcare interventions
  • Economic policy analysis
  • A/B testing optimization
  • Marketing attribution
  • Drug discovery
  • Social science research

We welcome all innovative approaches in causal AI, from theoretical frameworks to practical implementations in real-world applications.

Featured Publications Program

Each month, we select outstanding causal AI publications to feature on our platform. Featured publications receive:

  • Prominent visibility on Ready Tensor's homepage and causal AI category
  • Social media promotion to our community of AI professionals
  • Digital certificate of recognition
  • Cash prize of $200 for exceptional publications

Publications are evaluated based on technical innovation, implementation quality, and practical impact.

All public causal AI publications are automatically considered for this recognition program.

Note: Ready Tensor employees and contractors may contribute publications but are not eligible for cash prizes.

Ready to Showcase Your Project?

Share Your Causal ML Innovation

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Types of Publications

From foundational explorations to advanced research, we welcome causal AI publications that advance understanding and practical applications in the field. Share your work to help build a comprehensive knowledge base for the causal AI community.

Research Contributions:

  • Original research in causal inference methods
  • Surveys of causal discovery techniques
  • Comparative analyses of causal estimation approaches
  • Novel datasets for causal learning evaluation
  • Reproducibility studies of causal methods

Implementation & Applications:

  • Real-world causal analysis case studies
  • Deployment guides for causal inference tools
  • Framework implementations and examples
  • Scalable causal discovery solutions
  • Competition solution write-ups and analyses

Open Source & Independent Projects:

  • Open-source causal inference libraries
  • Tools for causal discovery and estimation
  • Personal exploration projects
  • Side projects implementing novel methods
  • Custom implementations of research papers

Educational & Academic:

  • Academic research implementations
  • Graduate thesis projects
  • Interactive causal analysis tutorials
  • Course projects and assignments
  • Practical guides and learning resources

How to Publish

  1. Create a free Ready Tensor account if you don't already have one.
  1. To create a new publication, click on 'Create New' and then 'New Publication' from the left menu.
  1. Follow the intuitive workflow. You can copy/paste content in markdown style, and even upload content from your Jupyter Notebooks. It's fast and easy.
  1. Tag your publication with relevant keywords like 'causal-ai', 'causal-inference', or 'counterfactual-analysis' to help others discover your work.
  1. Preview your work and click 'Publish' to share it with the community.

Maximize Your Chances of Being Featured

To create a publication that stands out, we highly recommend reviewing our comprehensive best practices guide before starting your publication. The guide will help you:

  • Choose the most appropriate format for your causal AI project
  • Structure your content effectively for your chosen project type
  • Understand the technical criteria our judges look for
  • Apply proven techniques for enhancing readability and visual appeal

Access our complete best practices guide here: Engage and Inspire: Best Practices for Publishing on Ready Tensor

Pro tip: While writing your publication, keep the guide open in another tab. Even implementing a few of its recommendations can significantly improve your publication's impact and chances of being featured.

Join the Community of Causal Learning Innovators

Share Your Causal AI Innovation

Start Your Publication