Layer-Neighbor Sampling — Defusing Neighborhood Explosion in GNNs |
NIPS 2023 |
Sampling |
Paper |
Code |
Efficient Learning of Linear Graph Neural Networks via Node Subsampling |
NIPS 2023 |
Sampling |
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Communication-Free Distributed GNN Training with Vertex Cut |
Arxiv 2023 |
Distributed |
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DSpar: An Embarrassingly Simple Strategy for Efficient GNN Training and Inference via Degree-based Sparsification |
TMLR 2023 |
Data-driven, Graph Condensation |
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Learning Large Graph Property Prediction via Graph Segment Training |
Arxiv 2023 |
Graph Transformer |
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LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation |
ICML 2023 |
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Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication |
ICML 2023 |
Distributed |
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GOAT: A Global Transformer on Large-scale Graphs |
ICML 2023 |
Graph Transformer |
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Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks |
ICML 2023 |
NAS |
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Fast Online Node Labeling for Very Large Graphs |
ICML 2023 |
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Graph Neural Tangent Kernel: Convergence on Large Graphs |
ICML 2023 |
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RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations |
ICML 2022 |
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LMC: FAST TRAINING OF GNNS VIA SUBGRAPH-WISE SAMPLING WITH PROVABLE CONVERGENCE |
ICLR 2023 |
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MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization |
ICLR 2023 |
GNN as MLP |
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Influence-Based Mini-Batching for Graph Neural Networks |
LOG 2022 |
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GraphFM: Improving Large-Scale GNN Training via Feature Momentum |
NIPS 2022 |
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A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking |
NIPS 2022 |
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ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective |
NIPS 2022 |
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Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity |
NIPS 2022 |
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Graph Condensation for Graph Neural Networks |
ICLR 2022 |
Data-driven, Graph Condensation |
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Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation |
ICLR 2022 |
GNN as MLP |
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EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression |
ICLR 2022 |
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SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs |
KDD 2022 |
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Graph Condensation via Receptive Field Distribution Matching |
Arxiv 2022 |
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GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings |
ICML 2021 |
Large Graph, Sampling |
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A Unified Lottery Ticket Hypothesis for Graph Neural Networks |
ICML 2021 |
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VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization |
NIPS 2021 |
Quantization |
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