Alternatives and similar repositories for gde

Users that are interested in gde are comparing it to the libraries listed below

• twitter-research / graph-neural-pde
  Graph Neural PDEs
  ☆333Updated 2 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆58Updated 10 months ago
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆61Updated 4 years ago
• mbilos / neural-flows-experiments
  Experiments for Neural Flows paper
  ☆97Updated 3 years ago
• facebookresearch / neural_stpp
  Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domain…
  ☆106Updated 3 years ago
• jliu / graph-normalizing-flows
  Code for Graph Normalizing Flows.
  ☆63Updated 5 years ago
• DeepGraphLearning / ContinuousGNN
  ☆47Updated 3 years ago
• calvin-zcx / ndcn
  Neural Dynamics on Complex Networks
  ☆53Updated 4 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆73Updated 3 years ago
• FerranAlet / graph_element_networks
  ☆57Updated 2 years ago
• Rachnog / Neural-ODE-Experiments
  This repository contains experiments with Neural Ordinary Differential Equations with simulated and real empirical data
  ☆200Updated 6 years ago
• cagatayyildiz / ODE2VAE
  ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
  ☆129Updated 11 months ago
• YuliaRubanova / latent_ode
  Code for "Latent ODEs for Irregularly-Sampled Time Series" paper
  ☆560Updated 4 years ago
• ermongroup / GraphScoreMatching
  Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling
  ☆111Updated 2 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆36Updated 5 years ago
• stefaniaebli / simplicial_neural_networks
  Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called si…
  ☆79Updated 4 years ago
• lucfra / LDS-GNN
  Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)
  ☆197Updated last year
• USC-Melady / ICLR2020-PADGN
  Official PyTorch implementation of "Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics" (https://openreview.net/forum…
  ☆51Updated 5 years ago
• gasteigerjo / gdc
  Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)
  ☆273Updated 2 years ago
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆216Updated 3 years ago
• twitter-research / neural-sheaf-diffusion
  ☆78Updated last year
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆171Updated 3 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 years ago
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆117Updated 2 years ago
• Haggaim / InvariantGraphNetworks
  Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"
  ☆24Updated 5 years ago
• tk-rusch / GraphCON
  GraphCON (ICML 2022)
  ☆59Updated 2 years ago
• BorgwardtLab / TOGL
  Topological Graph Neural Networks (ICLR 2022)
  ☆124Updated 3 years ago
• SwiftieH / IGNN
  Implicit Graph Neural Networks
  ☆62Updated 3 years ago
• yincheng / GGP
  Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'
  ☆38Updated 6 years ago
• balcilar / Spectral-Designed-Graph-Convolutions
  Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper
  ☆50Updated 4 years ago