Alternatives and similar repositories for sparse_smoothing

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

• abojchevski / node_embedding_attack
  Adversarial Attacks on Node Embeddings via Graph Poisoning
  ☆60Updated 5 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 years ago
• danielzuegner / robust-gcn
  Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".
  ☆43Updated 4 years ago
• devnkong / FLAG
  Official implementation of our FLAG paper (CVPR2022)
  ☆145Updated 3 years ago
• PurdueMINDS / Equivalence
  Equivalence Between Structural Representations and Positional Node Embeddings
  ☆22Updated 5 years ago
• vikasverma1077 / GraphMix
  Code for reproducing results in GraphMix paper
  ☆72Updated 2 years ago
• SwiftieH / IGNN
  Implicit Graph Neural Networks
  ☆64Updated 3 years ago
• chentingpc / gfn
  Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"
  ☆53Updated 5 years ago
• tech-srl / bottleneck
  Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
  ☆96Updated 3 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 5 years ago
• claying / GCKN
  Pytorch Implementation of Graph Convolutional Kernel Networks
  ☆54Updated 2 years ago
• danielzuegner / gnn-meta-attack
  Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".
  ☆152Updated 3 years ago
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 4 years ago
• sigeisler / robustness_of_gnns_at_scale
  This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).
  ☆30Updated 2 years ago
• danielzuegner / robust-gcn-structure
  ☆12Updated 4 years ago
• chrsmrrs / sparsewl
  Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"
  ☆22Updated 3 years ago
• LingxiaoShawn / PairNorm
  Source code for PairNorm (ICLR 2020)
  ☆79Updated 5 years ago
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆84Updated last year
• cvignac / SMP
  ☆28Updated 4 years ago
• lxiaorui / ElasticGNN
  Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"
  ☆42Updated 4 years ago
• Kaixiong-Zhou / DGN
  Pytorch implementation of differentiable group normalization (NeurIPS 2020)
  ☆38Updated 4 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• tvayer / FGW
  Code for Optimal Transport for structured data with application on graphs
  ☆102Updated 2 years ago
• se-ok / WLsimilarity
  informal exposition of Weisfeiler-Leman similarity
  ☆28Updated 4 years ago
• leichen2018 / GNN-Substructure-Counting
  The official implementation of ''Can Graph Neural Networks Count Substructures?'' NeurIPS 2020
  ☆35Updated 4 years ago
• HongtengXu / Relational-Factorization-Model
  Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI-20)
  ☆31Updated 2 years ago
• Shen-Lab / SS-GCNs
  [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
  ☆111Updated 4 years ago
• HongtengXu / gwl
  Gromov-Wasserstein Learning for Graph Matching and Node Embedding
  ☆72Updated 6 years ago
• HekpoMaH / algorithmic-concepts-reasoning
  ☆25Updated 4 years ago
• VITA-Group / Deep_GCN_Benchmarking
  [TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*,…
  ☆125Updated 3 years ago