danielegrattarola / GNCA
Code for "Learning Graph Cellular Automata" (NeurIPS 2021).
☆66Updated 2 years ago
Alternatives and similar repositories for GNCA:
Users that are interested in GNCA are comparing it to the libraries listed below
- Representation Learning on Topological Domains☆79Updated this week
- ☆173Updated last year
- Official implementation of E(n)-equivariant Graph Neural Cellular Automata☆26Updated 10 months ago
- Computing on Topological Domains☆205Updated this week
- Official repository for the Topological Deep Learning Challenge 2024, organized by TAG-DS & PyT-Team and hosted by GRaM Workshop @ ICML 2…☆38Updated 3 weeks ago
- Graph neural networks in JAX.☆67Updated 8 months ago
- Differentiable Euler Characteristic Transform☆17Updated 8 months ago
- Official Implementation of the ICML 2023 paper: "Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally …☆70Updated last year
- The code for "Diffusion Geometry" (2024).☆40Updated 9 months ago
- Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called si…☆76Updated 3 years ago
- A topological machine learning framework based on PyTorch☆165Updated 6 months ago
- Topological Deep Learning☆256Updated this week
- Topological Graph Neural Networks (ICLR 2022)☆122Updated 2 years ago
- Code for paper E(n)-Equivariant Topological Neural Networks☆29Updated 3 months ago
- ☆63Updated last year
- Code repository of the paper "Clifford-Steerable Convolutional Neural Networks"☆47Updated 7 months ago
- ☆31Updated 7 months ago
- Code for "Manifold Diffusion Geometry: Curvature, Tangent Spaces, and Dimension"☆42Updated 4 months ago
- High performance implementation of Vietoris-Rips persistence.☆44Updated 9 months ago
- ☆176Updated last month
- Python-based persistent homology algorithms☆19Updated last year
- TopoBench is a Python library designed to standardize benchmarking and accelerate research in Topological Deep Learning☆107Updated this week
- Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…☆20Updated 2 years ago
- Mechanistically interpretable neurosymbolic AI (Nature Comput Sci 2024): losslessly compressing NNs to computer code and discovering new …☆84Updated last year
- Uncertainty and causal emergence in complex networks☆109Updated 3 years ago
- Code used by the "Clifford Group Equivariant Neural Networks" paper.☆80Updated 9 months ago
- Deep learning made topological.☆83Updated 7 months ago
- ☆37Updated 2 years ago
- Neural Graphical models are neural network based graphical models that offer richer representation, faster inference & sampling☆28Updated last year
- Curiosity driven exploration of your complex system 👀☆36Updated last month