Papers › GREAD: Graph Neural Reaction-Diffusion Networks

GREAD: Graph Neural Reaction-Diffusion Networks

25 Nov 2022arXiv:2211.14208archive 2025-07-28

Jeongwhan Choi, Seoyoung Hong, Noseong Park, Sung-Bae Cho

Graph neural networks (GNNs) are one of the most popular research topics for deep learning. GNN methods typically have been designed on top of the graph signal processing theory. In particular, diffusion equations have been widely used for designing the core processing layer of GNNs, and therefore they are inevitably vulnerable to the notorious oversmoothing problem. Recently, a couple of papers paid attention to reaction equations in conjunctions with diffusion equations. However, they all consider limited forms of reaction equations. To this end, we present a reaction-diffusion equation-based GNN method that considers all popular types of reaction equations in addition to one special reaction equation designed by us. To our knowledge, our paper is one of the most comprehensive studies on reaction-diffusion equation-based GNNs. In our experiments with 9 datasets and 28 baselines, our method, called GREAD, outperforms them in a majority of cases. Further synthetic data experiments show that it mitigates the oversmoothing problem and works well for various homophily rates.

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Code

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compute_enegry_evolution jeongwhanchoi/gread/src/base_classes.py official repository unverified Apache-2.0 (permissive) · 34b68102305cf124 · report
get_component jeongwhanchoi/gread/src/data.py official repository unverified Apache-2.0 (permissive) · c68140584cc0e991 · report
hetero_params jeongwhanchoi/gread/src/gread_params.py official repository unverified Apache-2.0 (permissive) · 5d74f163186ed970 · report
run_evaluator jeongwhanchoi/gread/src/early_stop_solver.py official repository unverified Apache-2.0 (permissive) · 78ac42cc931414c2 · report
shared_grand_params jeongwhanchoi/gread/src/gread_params.py official repository unverified Apache-2.0 (permissive) · 9258a750860491c6 · report
shared_gread_params jeongwhanchoi/gread/src/gread_params.py official repository unverified Apache-2.0 (permissive) · b55b354d7bbb6311 · report
threshold_mat jeongwhanchoi/gread/src/distances_kNN.py official repository unverified Apache-2.0 (permissive) · bc4f44e9386e89e5 · report
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get_optimizer identical code first harvested elsewhere ran · our draft was wrong licence of this copy not recorded · dab3444777a2e6c7 · report

Tasks

Node Classification

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Node Classification Chameleon (48%/32%/20% fixed splits) GREAD-BS Accuracy 67.98 #1 of 4 Archive leaderboard report
Node Classification Citeseer (48%/32%/20% fixed splits) GREAD-BS Accuracy 77.53 #26 of 26 Archive leaderboard report
Node Classification Cora (48%/32%/20% fixed splits) GREAD-BS Accuracy 88.39 #26 of 26 Archive leaderboard report
Node Classification Cornell (48%/32%/20% fixed splits) GREAD-AC Accuracy 87.03 #1 of 3 Archive leaderboard report
Node Classification Cornell (48%/32%/20% fixed splits) GREAD-BS Accuracy 86.22 #2 of 3 Archive leaderboard report
Node Classification Cornell (48%/32%/20% fixed splits) GREAD-F Accuracy 85.41 #3 of 3 Archive leaderboard report
Node Classification Film(48%/32%/20% fixed splits) GREAD-BS Accuracy 37.49 #1 of 1 Archive leaderboard report
Node Classification PubMed (48%/32%/20% fixed splits) GREAD-BS Accuracy 90.21 #26 of 26 Archive leaderboard report
Node Classification Squirrel (48%/32%/20% fixed splits) GREAD-BS Accuracy 51.01 #1 of 4 Archive leaderboard report
Node Classification Texas (48%/32%/20% fixed splits) GREAD-F Accuracy 88.11 #1 of 2 Archive leaderboard report
Node Classification Texas (48%/32%/20% fixed splits) GREAD-BS Accuracy 87.57 #2 of 2 Archive leaderboard report
Node Classification Wisconsin (48%/32%/20% fixed splits) GREAD-BS Accuracy 88.04 #1 of 2 Archive leaderboard report
Node Classification Wisconsin (48%/32%/20% fixed splits) GREAD-F Accuracy 86.47 #2 of 2 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

DiffusionGCNNODE

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