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Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications

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Graph Diffusion Models: A Comprehensive Survey of Methods and Applications

This is the summation of all the methods, datasets, and other survey mentioned in our survey ‘Graph Diffusion Models: A Comprehensive Survey of Methods and Applications’ 🔥. Any problems, please contact shouyuntao@stu.xjtu.edu.cn. Any other interesting papers or codes are welcome. If you find this repository useful to your research or work, it is really appreciated to star this repository ❤️.

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Contents

Molecule generation

De novo molecule design

Methods Paper Code Methods Paper Code
DiGress (ICLR-23) [paper] [code] MiDi (ICLR-23) [paper] [code]
CDGS (NeurIPS-22) [paper] [code] GCDM (ICLR-23) [paper] [code]
EDM (ICML-22) [paper] [code] Wu et al. (NeurIPS-22) [paper] –
MDM (AAAI-23) [paper] [code] DiffLinker [paper] [code]
JODO [paper] [code] SILVR [paper] –
HierDiff (ICML-23) [paper] [code] – – –
BIMODAL [paper] [code] RationaleRL (ICML20) [paper] [code]
GEOLDM (ICML-23) [paper] [code] MGM [paper] –
LFM AISTATS-20 [paper] [code] RetMol [paper] [code]
MolGPT [paper] – Bridge (NeurIPS-2022) [paper] –
Bresson et al. [paper] – FLAG (ICLR-23) [paper] [code]
LIMO [paper] [code] D3FG NeurIPS-24 [paper] [code]

Conformation design

Methods Paper Code Methods Paper Code
ConfGF (ICML-21) [paper] [code] DGSM (NeurIPS-21) [paper] –
GeoDiff (ICLR-22) [paper] [code] ColfNet (ICML-22) [paper] –
Torsion Diffusion (NeurIPS-22) [paper] [code] DiffMD (AAAI-23) [paper] –
RINGER [paper] – – – –

De novo ligand design

Methods Paper Code Methods Paper Code
DiffBP [paper] – DiffSBDD [paper] –
TargetDiff (ICLR-23) [paper] – PMDM [paper] –
D3FG [paper] – – – –

Ligand docking

Methods Paper Code
DIFFDOCK (NeurIPS-22) [paper] –
EDM-Dock (JCIM) [paper] [code]
DPL [paper] [code]
NeuralPLexer [paper] –
E3BIND (ICLR-23) [paper] –

Protein design

Methods Paper Code Methods Paper Code
DiffAb (NeurIPS-22) [paper] – Anand [paper] –
PROTSEED (ICLR-23) [paper] – ProteinSGM [paper] [code]
SMCDiff (ICLR-23) [paper] [code] GraDe-IF [paper] –
EigenFold [paper] [code] – – –
CGM (NeurIPS-19) [paper] [code] SeqDesign [paper] [code]
Fold2Seq (ICML-21) [paper] [code] EvoDiff [paper] –
GVP （ICLR-21） [paper] [code] ESM (NeurIPS-21) [paper] –

Motion generation

Motion synthesis

Methods Paper Code Homepage Methods Paper Code Homepage
MotionDiffuse [paper] [code] [homepage] Modiff [paper] – –
Ren et al. (ICASSP-23) [paper] – – FLAME (AAAI-23) [paper] – –
MoFusion (CVPR-23) [paper] – [homepage] MDM (ICLR-23) [paper] [code] [homepage]
MLD (CVPR-23) [paper] [code] [homepage] PriorMDM [paper] [code] [homepage]
Alexanderson et al. (ACM Trans. Graph.) [paper] – – EDGE (CVPR-23) [paper] [code] [homepage]
SceneDiffuser [paper] [code] [homepage] MoDi (CVPR-23) [paper] [code] [homepage]
BiGraphDiff [paper] – – DiffuPose [paper] – –

Motion prediction

Methods Paper Code Homepage
Ahn et al. (ICRA-23) [paper] [code] [homepage]
HumanMAC [paper] [code] [homepage]
TCD (ICRA-23) [paper] [code] –
DiffMotion [paper] – –

Others

Methods Paper Code Homepage Methods Paper Code Homepage
EDP-GNN [paper] – – GSDM [paper] – –
NVDiff [paper] – – DPM-GSP [paper] – –
DiffSTG [paper] – – DIFUSCO [paper] – –
GraphGDP [paper] [code] – HouseDiffusion (CVPR-23) [paper] [code] [homepage]
NAP [paper] – [homepage] EDGE [paper] – –
DruM [paper] – – DDM [Paper] – –
DiffusionNAG [paper] – – TSDiff [paper] – –
GraphArm [paper] – – HGDM [paper] [code] –
Lee et al. [paper] – – SaGess [paper] – –
SLD [paepr] – – Diff-POI [paper] – –
Brain Diffuser [paper] – – Lu et al. [paper] – –
GBD [paper] [code] – DiffGraph [paper] [code] –
ProGDM [paper] [code] – R-ode [paper] – –

Datasets

Dataset Dimensionality Category No.of Graphs (G) No. of Nodes (N)
Community-small 2D Social 100 11 < N < 20
Ego-small 2D Social 200 3 < N < 18
Grid 2D Grid 100 N <= 400
QM9 3D Bioinformatics/Molecular 130,831 3 < N < 29
ZINC250K 3D Bioinformatics/Molecular 249,456 6 < N < 38
Enzymes 3D Bioinformatics/Protein 600 9 < N < 125
SBM-27 2D Social 200 24 < N < 27
Planar-60 2D Social 200 N = 60
AIDS 2D Bioinformatics/Molecular 2000 –
Synthie 2D Social 300 N = 100
Proteins 3D Bioinformatics/Protein 1113 N = 39.1

Molecule generation

Methods Paper Source Methods Paper Source
Zinc [paper] [source] GEOM-QM9 [paper] [source]
GEOM-Drugs [paper] [source] CrossDocked2020 [paper] [source]
BioLiP [paper] [source] PDBBind [paper] [source]
SAbDab [paper] [source] – – –

Motion generation

Methods Paper Source Methods Paper Source
Human3.6M [paper] [source] HumanEva-I [paper] [source]
HumanAct12 [paper] [source] HumanML3D [paper] [source]
KIT [paper] [source] BABEL [paper] [source]
UESTC [paper] [source] 3DPW [paper] [source]
NTU RGB+D [paper] [source] AIST++ [paper] [source]
TSG [paper] [source] ZeroEGGS [paper] [source]

Other surveys

Paper Url Source
Diffusion-based Graph Generative Methods [paper] [source]
Diffusion Models: A Comprehensive Survey of Methods and Applications [paper] [source]
A Survey on Generative Diffusion Model [paper] [source]
Generative Diffusion Models on Graphs: Methods and Applications [paper] –
A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material [paper] –
Graph-based Molecular Representation Learning [paper] –
Generative Models as an Emerging Paradigm in the Chemical Sciences [paper] –
A Survey on Deep Graph Generation: Methods and Applications (LoG-22) [paper] –
A Survey on Temporal Graph Representation Learning and Generative Modeling [paper] –
Human motion modeling with deep learning: A survey [paper] –
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design [paper] –

Acknowledgement ❤️

Thanks to Diffusion-based-Graph-Generative-Methods.

Star History

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Visit original content creator repository https://github.com/yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications

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