🌐 TopoX 🍩#

TopoX are a set of Python packages for meeting diverse computational needs on topological domains. Topological domains are the natural mathematical structures representing relations between the components of a dataset.

natural shapes

Many natural systems as diverse as social networks and proteins are characterized by relational structure. This is the structure of interactions between components in the system, such as social interactions between individuals or electrostatic interactions between atoms.

TopoX provides a unifying interface to compute and learn with such relational data.

🎯 Scope and functionality#

TopoX are a set of packages for computing with topological domains and studying their properties.

It consists of three different packages:

  • TopoNetX (TNX) which introduces a NetworkX like interface for topological domains.

    Jump to detailed documentation for TopoNetX.

  • TopoModelX (TMX) which implements deep learning on topological domains.

    Jump to detailed documentation for the TopoModelX.

  • TopoEmbedX (TEX) which provides methods for generating embeddings on topological domains.

    Jump to detailed documentation for the TopoEmbedX.

🔍 References#

To learn more about how topological domains are used in deep learning:

  • Mustafa Hajij, Ghada Zamzmi, Theodore Papamarkou, Nina Miolane, Aldo Guzmán-Sáenz, Karthikeyan Natesan Ramamurthy, Tolga Birdal, Tamal K. Dey, Soham Mukherjee, Shreyas N. Samaga, Neal Livesay, Robin Walters, Paul Rosen, Michael T. Schaub. Topological Deep Learning: Going Beyond Graph Data.

      title={Topological Deep Learning: Going Beyond Graph Data},
      author={Mustafa Hajij and Ghada Zamzmi and Theodore Papamarkou and Nina Miolane and Aldo Guzmán-Sáenz and Karthikeyan Natesan Ramamurthy and Tolga Birdal and Tamal K. Dey and Soham Mukherjee and Shreyas N. Samaga and Neal Livesay and Robin Walters and Paul Rosen and Michael T. Schaub},
      title={Architectures of Topological Deep Learning: A Survey on Topological Neural Networks},
      author={Mathilde Papillon and Sophia Sanborn and Mustafa Hajij and Nina Miolane},