Alternatives and similar repositories for bottleneck

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

• DevinKreuzer / SAN
  ☆156Updated 3 years ago
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆81Updated 9 months ago
• gbouritsas / GSN
  Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…
  ☆101Updated 3 years ago
• SwiftieH / IGNN
  Implicit Graph Neural Networks
  ☆62Updated 3 years ago
• vijaydwivedi75 / lrgb
  Long Range Graph Benchmark, NeurIPS 2022 Track on D&B
  ☆157Updated last year
• chrsmrrs / sparsewl
  Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"
  ☆22Updated 3 years ago
• CUAI / Non-Homophily-Benchmarks
  [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs
  ☆113Updated 3 years ago
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 4 years ago
• beabevi / ESAN
  Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)
  ☆89Updated 2 years ago
• Haggaim / InvariantGraphNetworks
  Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"
  ☆24Updated 5 years ago
• uoguelph-mlrg / GGM-metrics
  Official repository for the paper "On Evaluation Metrics for Graph Generative Models"
  ☆25Updated 3 years ago
• twitter-research / sign
  SIGN: Scalable Inception Graph Network
  ☆97Updated 4 years ago
• Saro00 / DGN
  Implementation of Directional Graph Networks in PyTorch and DGL
  ☆118Updated 4 years ago
• LingxiaoShawn / GNNAsKernel
  Source code for From Stars to Subgraphs (ICLR 2022)
  ☆70Updated last year
• chrsmrrs / tudataset
  ☆94Updated 2 years ago
• cvignac / SMP
  ☆28Updated 3 years ago
• KarolisMart / DropGNN
  The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)
  ☆26Updated 2 years ago
• mims-harvard / G-Meta
  Graph meta learning via local subgraphs (NeurIPS 2020)
  ☆123Updated 10 months ago
• jianhao2016 / GPRGNN
  ☆135Updated last year
• vijaydwivedi75 / gnn-lspe
  Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
  ☆257Updated 3 years ago
• a-lucic / cf-gnnexplainer
  ☆58Updated 3 years ago
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆53Updated 2 years ago
• rusty1s / pyg_autoscale
  Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch
  ☆164Updated 2 years ago
• karl-zhao / benchmarking-gnns-pyg
  ☆31Updated 2 years ago
• gasteigerjo / gdc
  Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)
  ☆272Updated 2 years ago
• jctops / understanding-oversquashing
  ☆40Updated 2 years ago
• LingxiaoShawn / PairNorm
  Source code for PairNorm (ICLR 2020)
  ☆77Updated 5 years ago
• balcilar / gnn-spectral-expressive-power
  Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021
  ☆46Updated 3 years ago
• facebookresearch / shaDow_GNN
  [NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architec…
  ☆134Updated 3 years ago
• Chen-Cai-OSU / GNN-Over-Smoothing
  A Note On Over-Smoothing for Graph Neural Network
  ☆20Updated 4 years ago