Alternatives and similar repositories for Mila-Graph-Reading-Group

Users that are interested in Mila-Graph-Reading-Group are comparing it to the libraries listed below

• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 years ago
• karl-zhao / benchmarking-gnns-pyg
  ☆31Updated 2 years ago
• jacobdeasy / geometric-js
  ☆18Updated 4 years ago
• crisbodnar / dgm
  Deep Graph Mapper: Seeing Graphs through the Neural Lens
  ☆58Updated 2 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆37Updated 5 years ago
• aniruddhraghu / meta-pretraining
  Code accompanying paper: Meta-Learning to Improve Pre-Training
  ☆37Updated 4 years ago
• CalculatedContent / ImplicitSelfRegularization
  Repo to accompany paper "Implicit Self-Regularization in Deep Neural Networks..."
  ☆47Updated 6 years ago
• HazyResearch / HypHC
  Hyperbolic Hierarchical Clustering.
  ☆206Updated 2 years ago
• NNReasoning / What-Can-Neural-Networks-Reason-About
  ☆44Updated 5 years ago
• emilemathieu / pvae
  code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".
  ☆129Updated 2 years ago
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆104Updated 5 years ago
• oskopek / mvae
  Mixed-curvature Variational Autoencoders (ICLR 2020)
  ☆65Updated 4 years ago
• SwiftieH / IGNN
  Implicit Graph Neural Networks
  ☆64Updated 4 years ago
• nd7141 / graph_datasets
  Data for "Understanding Isomorphism Bias in Graph Data Sets" paper.
  ☆91Updated 6 years ago
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆98Updated 3 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 5 years ago
• lsj2408 / GraphNorm
  [ICML 2021] GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training (official implementation)
  ☆107Updated 3 years ago
• twitter-research / sign
  SIGN: Scalable Inception Graph Network
  ☆95Updated 5 years ago
• nalexai / hyperlib
  Library that contains implementations of machine learning components in the hyperbolic space
  ☆144Updated last year
• claying / GCKN
  Pytorch Implementation of Graph Convolutional Kernel Networks
  ☆54Updated 3 years ago
• PurdueMINDS / RelationalPooling
  ☆35Updated 6 years ago
• drewwilimitis / hyperbolic-learning
  Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)
  ☆143Updated 5 years ago
• nkeriven / random-graph-gnn
  ☆12Updated 4 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆43Updated 3 years ago
• yichousun / Winter2021_CS249_GNN
  ☆54Updated 3 years ago
• nimadehmamy / Understanding-GCN
  code for the paper in NeurIPS 2019
  ☆40Updated 2 years ago
• dalab / hyperbolic_nn
  Source code for the paper "Hyperbolic Neural Networks", https://arxiv.org/abs/1805.09112
  ☆182Updated 5 years ago
• SagiLevanon1 / scmp
  ☆10Updated 4 years ago
• arrigonialberto86 / set_transformer
  A TensorFlow implementation of the paper 'Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks'
  ☆31Updated last year
• se-ok / WLsimilarity
  informal exposition of Weisfeiler-Leman similarity
  ☆28Updated 4 years ago