Zymrael / gde
Neural Graph Differential Equations (Neural GDEs)
☆198Updated 3 years ago
Alternatives and similar repositories for gde:
Users that are interested in gde are comparing it to the libraries listed below
- Graph Neural PDEs☆326Updated 2 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆57Updated 4 months ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆58Updated 4 years ago
- Experiments for Neural Flows paper☆93Updated 3 years ago
- Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling☆110Updated last year
- Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domain…☆102Updated 3 years ago
- ☆45Updated 3 years ago
- Code for Graph Normalizing Flows.☆62Updated 5 years ago
- Code for "Latent ODEs for Irregularly-Sampled Time Series" paper☆540Updated 4 years ago
- GraphCON (ICML 2022)☆59Updated 2 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆194Updated 11 months ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆103Updated 5 years ago
- ☆55Updated 2 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆268Updated last year
- Message Passing Neural Networks for Simplicial and Cell Complexes☆158Updated last year
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆426Updated last year
- Variational Graph Recurrent Neural Networks - PyTorch☆116Updated 4 years 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
- This repository contains code released by DiffEqML Research☆85Updated 2 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆115Updated last year
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆345Updated 2 years ago
- Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022☆250Updated 3 years ago
- Implementation of Directional Graph Networks in PyTorch and DGL☆117Updated 3 years ago
- Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".☆185Updated 2 years ago
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆86Updated last year
- The simplest pytorch implement (100 lines) of "Neural Ordinary Differential Equations" @ NeurIPS 2018 Best Paper.☆74Updated 4 years ago
- ☆40Updated 2 years ago
- This repository contains experiments with Neural Ordinary Differential Equations with simulated and real empirical data☆197Updated 5 years ago
- Collection of resources about partial differential equations, graph neural networks, deep learning and dynamical system simulation☆92Updated 2 years ago