Alternatives and similar repositories for LayerDAG

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

• Graph-COM / Pair-Align
  [ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)
  ☆14Updated last year
• KarolisMart / SPECTRE
  Reference implementation for SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators (ICML …
  ☆26Updated 3 years ago
• lsj2408 / Graphormer-GD
  [ICLR 2023 notable top-5%] Rethinking the Expressive Power of GNNs via Graph Biconnectivity (official implementation)
  ☆103Updated 2 years ago
• Graph-COM / GSAT
  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
  ☆168Updated last year
• LiamMa / GRIT
  This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".
  ☆127Updated last month
• divelab / GOOD
  GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]
  ☆202Updated 7 months ago
• luis-mueller / probing-graph-transformers
  Code for our paper "Attending to Graph Transformers"
  ☆90Updated last year
• RexYing / Rex-Ying-Thesis
  Rex Ying's Ph.D. Thesis, Stanford University
  ☆41Updated 3 years ago
• ykiiiiii / ACMP
  ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks(ICLR 2023)
  ☆20Updated last year
• Chen-Cai-OSU / MPNN-GT-Connection
  ☆21Updated 2 years ago
• GraphPKU / PygHO
  A library for subgraph GNN based on pyg
  ☆40Updated 9 months ago
• zaixizhang / ANS-GT
  NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"
  ☆52Updated last year
• tufts-ml / graph-generation-EDGE
  EDGE: Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling
  ☆65Updated 3 months ago
• Graph-COM / GESS
  Code for GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts
  ☆16Updated 8 months ago
• XiaoxinHe / neurips2023_learning_on_graphs
  List of papers on NeurIPS2023
  ☆89Updated last year
• mengliu1998 / DL4DisassortativeGraphs
  Papers about developing DL methods on disassortative graphs
  ☆48Updated 3 years ago
• LingxiaoShawn / GNNAsKernel
  Source code for From Stars to Subgraphs (ICLR 2022)
  ☆69Updated last year
• muhanzhang / NestedGNN
  ☆58Updated 3 years ago
• shamim-hussain / egt_pytorch
  Edge-Augmented Graph Transformer
  ☆80Updated last year
• chr26195 / PMLP
  This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…
  ☆89Updated last year
• vijaydwivedi75 / lrgb
  Long Range Graph Benchmark, NeurIPS 2022 Track on D&B
  ☆158Updated last year
• G-Taxonomy-Workgroup / GPSE
  Graph Positional and Structural Encoder
  ☆53Updated 8 months ago
• snap-stanford / conformalized-gnn
  Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)
  ☆82Updated 2 years ago
• uoguelph-mlrg / GGM-metrics
  Official repository for the paper "On Evaluation Metrics for Graph Generative Models"
  ☆25Updated 3 years ago
• ChenJY-Count / PolyGCL
  PyTorch implementation of "PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters"
  ☆15Updated last year
• Graph-COM / ED-HNN
  [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
  ☆48Updated last year
• emalgorithm / directed-graph-neural-network
  Dir-GNN is a machine learning model that enables learning on directed graphs.
  ☆81Updated 2 years ago
• ShichangZh / GStarX
  [NeurIPS 2022] Explaining Graph Neural Networks with Structure-Aware Cooperative Games (GStarX)
  ☆13Updated 2 years ago
• ivam-he / BernNet
  PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"
  ☆56Updated 2 years ago
• CurryTang / Towards-graph-foundation-models
  ☆89Updated last year