├── README.md
└── fig
    ├── clas.png
    ├── diffusionshuoming.png
    ├── methods.jpg
    └── readme.md


/README.md:
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  1 | [stars-img]: https://img.shields.io/github/stars/yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications?color=yellow
  2 | [stars-url]: https://github.com/yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications/stargazers
  3 | [fork-img]: https://img.shields.io/github/forks/yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications?color=lightblue&label=fork
  4 | [fork-url]: https://github.com/yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications/network/members
  5 | [AKGR-url]: https://github.com/yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications
  6 | 
  7 | # Graph Diffusion Models: A Comprehensive Survey of Methods and Applications
  8 | 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' :fire:. 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 :heart:.
  9 | 
 10 | [![GitHub stars][stars-img]][stars-url]
 11 | [![GitHub forks][fork-img]][fork-url]
 12 | 
 13 | <div  align="center"> 
 14 |   <img src="https://github.com/yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications/blob/main/fig/methods.jpg" width=100% />
 15 | </div>
 16 | 
 17 | <div  align="center"> 
 18 |   <img src="https://github.com/yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications/blob/main/fig/diffusionshuoming.png" width=100% />
 19 | </div>
 20 | 
 21 | <div  align="center"> 
 22 |   <img src="https://github.com/yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications/blob/main/fig/clas.png" width=100% />
 23 | </div>
 24 | 
 25 | 
 26 | ## Contents
 27 | - [Diffusion-based Graph Generative Methods](#diffusion-based-grap-generative-methods)
 28 |   - [Contents](#contents)
 29 |   - [Molecule generation](#molecule-generation)
 30 |     - [Molecule design](#de-novo-molecule-design)
 31 |     - [Conformation design](#conformation-design)
 32 |     - [De novo ligand design](#de-novo-ligand-design)
 33 |     - [Ligand docking](#ligand-docking)
 34 |     - [Protein design](#protein-design)
 35 |   - [Motion generation](#motion-generation)
 36 |     - [Motion synthesis](#motion-synthesis)
 37 |     - [Motion prediction](#motion-prediction)
 38 |   - [Others](#others)
 39 |   - [Datasets](#datasets)
 40 |     - [Molecule generation](#molecule-generation-1)
 41 |     - [Motion generation](#motion-generation-1)
 42 |   - [Other surveys](#other-surveys)
 43 | 
 44 | 
 45 | ## Molecule generation
 46 | 
 47 | ### De novo molecule design
 48 | | Methods | Paper | Code | Methods | Paper | Code |
 49 | | :----: | :----: | :----: | :----: | :----: | :----: |
 50 | | DiGress (ICLR-23) | [[paper]](https://arxiv.org/abs/2209.14734) | [[code]](https://github.com/cvignac/DiGress) | MiDi (ICLR-23) | [[paper]](https://openreview.net/forum?id=M6Ifac3G4HK) | [[code]](https://github.com/cvignac/MiDi) | 
 51 | | CDGS (NeurIPS-22) | [[paper]](https://openreview.net/forum?id=YD39Pw2HXBXM) | [[code]](https://github.com/GRAPH-0/CDGS) | GCDM (ICLR-23) | [[paper]](https://openreview.net/forum?id=X-tLu3OUE-d) | [[code]](https://github.com/BioinfoMachineLearning/bio-diffusion) |
 52 | | EDM (ICML-22) | [[paper]](https://proceedings.mlr.press/v162/hoogeboom22a.html) | [[code]](https://github.com/ehoogeboom/e3_diffusion_for_molecules) |  Wu et al. (NeurIPS-22) | [[paper]](https://openreview.net/forum?id=QagNEt9k8Vi) | - |
 53 | | MDM (AAAI-23) | [[paper]](https://arxiv.org/abs/2209.05710) | [[code]](https://github.com/tencent-ailab/MDM) | DiffLinker | [[paper]](https://openreview.net/forum?id=viZ4G1WZxh) | [[code]](https://github.com/igashov/DiffLinker) |
 54 | | JODO | [[paper]](https://doi.org/10.48550/arXiv.2305.12347) | [[code]](https://github.com/GRAPH-0/JODO)| SILVR | [[paper]](https://doi.org/10.48550/arXiv.2304.10905) | - |
 55 | | HierDiff (ICML-23) | [[paper]](https://proceedings.mlr.press/v202/qiang23a.html) | [[code]](https://github.com/qiangbo1222/HierDiff) | - | - | - |
 56 | | BIMODAL | [[paper]](https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.9b00943) | [[code]](https://github.com/ETHmodlab/BIMODAL) |  RationaleRL (ICML20) | [[paper]](https://proceedings.mlr.press/v119/jin20b/jin20b.pdf) | [[code]](https://github.com/wengong-jin/multiobj-rationale) |
 57 | | GEOLDM (ICML-23) | [[paper]](https://proceedings.mlr.press/v202/xu23n/xu23n.pdf)| [[code]](https://github.com/MinkaiXu/GeoLDM) | MGM | [[paper]](https://www.nature.com/articles/s41467-021-23415-2.pdf)| -|
 58 | | LFM AISTATS-20| [[paper]](https://proceedings.mlr.press/v108/podda20a/podda20a.pdf) | [[code]](https://github.com/marcopodda/fragment-based-dgm) | RetMol | [[paper]](https://arxiv.org/pdf/2208.11126) | [[code]](https://github.com/NVlabs/RetMol) |
 59 | | MolGPT | [[paper]](https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/60c7588e469df48597f456ae/original/lig-gpt-molecular-generation-using-a-transformer-decoder-model.pdf) | - | Bridge (NeurIPS-2022) | [[paper]](https://proceedings.neurips.cc/paper_files/paper/2022/file/eccc6e11878857e87ec7dd109eaa9eeb-Paper-Conference.pdf) | - |
 60 | | Bresson et al. | [[paper]](https://arxiv.org/pdf/1906.03412) | - | FLAG (ICLR-23) | [[paper]](https://openreview.net/pdf?id=Rq13idF0F73) | [[code]](https://github.com/zaixizhang/FLAG) |
 61 | | LIMO | [[paper]](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9527083/) | [[code]](https://github.com/Rose-STL-Lab/LIMO) | D3FG NeurIPS-24 | [[paper]](https://proceedings.neurips.cc/paper_files/paper/2023/file/6cdd4ce9330025967dd1ed0bed3010f5-Paper-Conference.pdf) | [[code]](https://github.com/EDAPINENUT/CBGBench/tree/master) |
 62 | 
 63 | ### Conformation design
 64 | | Methods | Paper | Code | Methods | Paper | Code |
 65 | | :----: | :----: | :----: | :----: | :----: | :----: |
 66 | | ConfGF (ICML-21) | [[paper]](https://proceedings.mlr.press/v139/shi21b.html) | [[code]](https://github.com/DeepGraphLearning/ConfGF) | DGSM (NeurIPS-21) | [[paper]](https://proceedings.neurips.cc/paper_files/paper/2021/file/a45a1d12ee0fb7f1f872ab91da18f899-Paper.pdf) | - | 
 67 | | GeoDiff (ICLR-22) | [[paper]](https://openreview.net/forum?id=PzcvxEMzvQC) | [[code]](https://github.com/MinkaiXu/GeoDiff) | ColfNet (ICML-22) | [[paper]](https://proceedings.mlr.press/v162/du22e.html) | - |
 68 | | Torsion Diffusion (NeurIPS-22) | [[paper]](https://openreview.net/forum?id=w6fj2r62r_H) | [[code]](https://github.com/gcorso/torsional-diffusion) | DiffMD (AAAI-23) | [[paper]](https://ojs.aaai.org/index.php/AAAI/article/view/25663) | - |
 69 | | RINGER| [[paper]](https://doi.org/10.48550/arXiv.2305.19800) | - | - | - | - |
 70 | ### De novo ligand design
 71 | | Methods | Paper | Code | Methods | Paper | Code |
 72 | | :----: | :----: | :----: | :----: | :----: | :----: |
 73 | | DiffBP | [[paper]](https://arxiv.org/abs/2211.11214) | - | DiffSBDD | [[paper]](https://arxiv.org/abs/2210.13695) | - | 
 74 | | TargetDiff (ICLR-23) | [[paper]](https://openreview.net/forum?id=kJqXEPXMsE0) | - | PMDM | [[paper]](https://www.biorxiv.org/content/early/2023/01/30/2023.01.28.526011) | - |
 75 | | D3FG | [[paper]](https://doi.org/10.48550/arXiv.2306.13769) | - | - | - | - |
 76 | ### Ligand docking
 77 | | Methods | Paper | Code |
 78 | | :----: | :----: | :----: |
 79 | | DIFFDOCK (NeurIPS-22) | [[paper]](https://openreview.net/forum?id=fky3a3F80if) | - |
 80 | | EDM-Dock (JCIM) | [[paper]](https://doi.org/10.1021/acs.jcim.2c01436) | [[code]](https://github.com/MatthewMasters/EDM-Dock) |
 81 | | DPL | [[paper]](https://doi.org/10.1186/s12859-023-05354-5) | [[code]](https://github.com/shuyana/DiffusionProteinLigand) |
 82 | | NeuralPLexer | [[paper]](https://doi.org/10.48550/arXiv.2209.15171) | - |
 83 | |  E3BIND (ICLR-23) | [[paper]](https://arxiv.org/pdf/2210.06069) | - |
 84 | 
 85 | 
 86 | 
 87 | ### Protein design
 88 | | Methods | Paper | Code | Methods | Paper | Code |
 89 | | :----: | :----: | :----: | :----: | :----: | :----: |
 90 | | DiffAb (NeurIPS-22) | [[paper]](https://openreview.net/forum?id=jSorGn2Tjg) | - | Anand | [[paper]](https://arxiv.org/abs/2205.15019) | - | 
 91 | | PROTSEED (ICLR-23) | [[paper]](https://openreview.net/forum?id=pRCMXcfdihq) | - | ProteinSGM | [[paper]](https://www.biorxiv.org/content/early/2023/02/04/2022.07.13.499967) | [[code]](https://gitlab.com/mjslee0921/proteinsgm) |
 92 | | SMCDiff (ICLR-23) | [[paper]](https://arxiv.org/abs/2206.04119) | [[code]](https://github.com/blt2114/ProtDiff_SMCDiff) | GraDe-IF | [[paper]](https://doi.org/10.48550/arXiv.2306.16819) | - |
 93 | | EigenFold | [[paper]](https://openreview.net/forum?id=BgbRVzfQqFp) | [[code]](https://github.com/bjing2016/EigenFold) | - | - | - |
 94 | | CGM (NeurIPS-19) | [[paper]](https://proceedings.neurips.cc/paper_files/paper/2019/file/f3a4ff4839c56a5f460c88cce3666a2b-Paper.pdf) | [[code]](https://github.com/jingraham/neurips19-graph-protein-design) | SeqDesign | [[paper]](https://www.nature.com/articles/s41467-021-22732-w) | [[code]](https://github.com/debbiemarkslab/SeqDesign) |
 95 | | Fold2Seq (ICML-21) | [[paper]](https://proceedings.mlr.press/v139/cao21a/cao21a.pdf) | [[code]](https://github.com/IBM/fold2seq) | EvoDiff | [[paper]](https://www.biorxiv.org/content/10.1101/2023.09.11.556673v1.full.pdf) | - |
 96 | | GVP （ICLR-21） | [[paper]](https://openreview.net/pdf?id=1YLJDvSx6J4) | [[code]](https://github.com/drorlab/gvp) | ESM (NeurIPS-21) | [[paper]](https://proceedings.neurips.cc/paper_files/paper/2021/file/f51338d736f95dd42427296047067694-Paper.pdf) | - |
 97 | 
 98 | ## Motion generation
 99 | 
100 | ### Motion synthesis
101 | | Methods | Paper | Code | Homepage | Methods | Paper | Code | Homepage |
102 | | :----: | :----: | :----: | :----: | :----: | :----: | :----: | :----: |
103 | | MotionDiffuse | [[paper]](https://arxiv.org/abs/2208.15001) | [[code]](https://github.com/mingyuan-zhang/MotionDiffuse) | [[homepage]](https://mingyuan-zhang.github.io/projects/MotionDiffuse.html) | Modiff | [[paper]](https://arxiv.org/abs/2301.03949) | - | - |
104 | | Ren et al. (ICASSP-23) | [[paper]](https://doi.org/10.1109/ICASSP49357.2023.10096441) | - | - | FLAME (AAAI-23) | [[paper]](https://arxiv.org/abs/2209.00349) | - | - |
105 | | MoFusion (CVPR-23) | [[paper]](https://openaccess.thecvf.com/content/CVPR2023/html/Dabral_Mofusion_A_Framework_for_Denoising-Diffusion-Based_Motion_Synthesis_CVPR_2023_paper.html) | - | [[homepage]](https://vcai.mpi-inf.mpg.de/projects/MoFusion/) | MDM (ICLR-23) | [[paper]](https://arxiv.org/abs/2209.14916) | [[code]](https://github.com/GuyTevet/motion-diffusion-model) | [[homepage]](https://guytevet.github.io/mdm-page/) |
106 | | MLD (CVPR-23) | [[paper]](https://openaccess.thecvf.com/content/CVPR2023/html/Chen_Executing_Your_Commands_via_Motion_Diffusion_in_Latent_Space_CVPR_2023_paper.html) | [[code]](https://github.com/chenfengye/motion-latent-diffusion) | [[homepage]](https://chenxin.tech/mld/) | PriorMDM | [[paper]](https://arxiv.org/abs/2303.01418) | [[code]](https://github.com/priorMDM/priorMDM) | [[homepage]](https://priormdm.github.io/priorMDM-page/) |
107 | | Alexanderson et al. (ACM Trans. Graph.) | [[paper]](https://arxiv.org/abs/2211.09707) | - | - | EDGE (CVPR-23) | [[paper]](https://openaccess.thecvf.com/content/CVPR2023/html/Tseng_EDGE_Editable_Dance_Generation_From_Music_CVPR_2023_paper.html) | [[code]](https://github.com/Stanford-TML/EDGE) | [[homepage]](https://edge-dance.github.io/) |
108 | | SceneDiffuser | [[paper]](https://arxiv.org/abs/2301.06015) | [[code]](https://github.com/scenediffuser/Scene-Diffuser) | [[homepage]](https://scenediffuser.github.io/) | MoDi (CVPR-23) | [[paper]](https://openaccess.thecvf.com/content/CVPR2023/html/Raab_MoDi_Unconditional_Motion_Synthesis_From_Diverse_Data_CVPR_2023_paper.html) | [[code]](https://github.com/sigal-raab/MoDi) | [[homepage]](https://sigal-raab.github.io/MoDi) |
109 | | BiGraphDiff | [[paper]](https://arxiv.org/abs/2301.10134) | - | - | DiffuPose | [[paper]](https://doi.org/10.48550/arXiv.2212.02796) | - | - |
110 | <!-- | - | [[paper]]() | - | - | - | [[paper]]() | - | - |
111 | | - | [[paper]]() | - | - | - | [[paper]]() | - | - | -->
112 | ### Motion prediction
113 | | Methods | Paper | Code | Homepage |
114 | | :----: | :----: | :----: | :----: |
115 | | Ahn et al. (ICRA-23) | [[paper]](https://arxiv.org/abs/2302.14503) | [[code]](https://github.com/cotton-ahn/diffusion-motion-prediction) | [[homepage]](https://sites.google.com/view/diffusion-motion-prediction) |
116 | | HumanMAC | [[paper]](https://arxiv.org/abs/2302.03665) | [[code]](https://github.com/LinghaoChan/HumanMAC) | [[homepage]](https://lhchen.top/Human-MAC/) |
117 | | TCD (ICRA-23) | [[paper]](https://doi.org/10.1109/ICRA48891.2023.10160399) | [[code]](https://github.com/vita-epfl/DePOSit) | - |
118 | | DiffMotion | [[paper]](https://doi.org/10.48550/arXiv.2305.12554) | - | - |
119 | 
120 | ## Others
121 | | Methods | Paper | Code | Homepage | Methods | Paper | Code | Homepage |
122 | | :----: | :----: | :----: | :----: | :----: | :----: | :----: | :----: |
123 | | EDP-GNN | [[paper]](https://proceedings.mlr.press/v108/niu20a.html) | - | - | GSDM | [[paper]](https://arxiv.org/abs/2211.08892) | - | - |
124 | | NVDiff | [[paper]](https://arxiv.org/abs/2211.10794) | - | - | DPM-GSP | [[paper]](https://arxiv.org/abs/2302.10506) | - | - |
125 | | DiffSTG | [[paper]](https://arxiv.org/abs/2301.13629) | - | - | DIFUSCO | [[paper]](https://arxiv.org/abs/2302.08224) | - | - |
126 | | GraphGDP | [[paper]](https://arxiv.org/abs/2212.01842) | [[code]](https://github.com/GRAPH-0/GraphGDP) | - | HouseDiffusion (CVPR-23) | [[paper]](https://openaccess.thecvf.com/content/CVPR2023/html/Shabani_HouseDiffusion_Vector_Floorplan_Generation_via_a_Diffusion_Model_With_Discrete_CVPR_2023_paper.html) | [[code]](https://github.com/aminshabani/house_diffusion) | [[homepage]](https://aminshabani.github.io/housediffusion/) |
127 | | NAP | [[paper]](https://arxiv.org/abs/2305.16315) | - | [[homepage]](https://www.cis.upenn.edu/~leijh/projects/nap/) | EDGE | [[paper]](https://arxiv.org/abs/2305.04111) | - | - |
128 | | DruM | [[paper]](https://arxiv.org/abs/2302.03596) | - | - | DDM | [[Paper]](https://arxiv.org/abs/2306.13210) | - | - |
129 | | DiffusionNAG | [[paper]](https://arxiv.org/abs/2305.16943) | - | - | TSDiff | [[paper]](https://doi.org/10.21203/rs.3.rs-2924237/v1) | - | - |
130 | | GraphArm | [[paper]](https://openreview.net/forum?id=98J48HZXxd5) | - | - | HGDM | [[paper]](https://doi.org/10.48550/arXiv.2306.07618) | [[code]](https://github.com/GRAPH-0/JODO) | - |
131 | | Lee et al. | [[paper]](https://doi.org/10.1080/15376494.2023.2198528) | - | - | SaGess | [[paper]](https://doi.org/10.48550/arXiv.2306.16827) | - | - |
132 | | SLD | [[paepr]](https://openreview.net/forum?id=AykEgQNPJEK) | - | - | Diff-POI | [[paper]](https://doi.org/10.48550/arXiv.2304.07041) | - | - |
133 | | Brain Diffuser | [[paper]](https://doi.org/10.48550/arXiv.2303.06410) | - | - | Lu et al. | [[paper]](https://doi.org/10.48550/arXiv.2304.05137) | - | - |
134 | 
135 | ## Datasets
136 | 
137 | |     Dataset     | Dimensionality |         Category         | No.of Graphs (G) | No. of Nodes (N) |
138 | |:---------------:|:--------------:|:------------------------:|:----------------:|:----------------:|
139 | | Community-small |       2D       |          Social          |        100       |    11 < N < 20   |
140 | |    Ego-small    |       2D       |          Social          |        200       |    3 < N < 18    |
141 | |       Grid      |       2D       |           Grid           |        100       |     N <= 400     |
142 | |       QM9       |       3D       | Bioinformatics/Molecular |      130,831     |    3 < N < 29    |
143 | |     ZINC250K    |       3D       | Bioinformatics/Molecular |      249,456     |    6 < N < 38    |
144 | |     Enzymes     |       3D       |  Bioinformatics/Protein  |        600       |    9 < N < 125   |
145 | |      SBM-27     |       2D       |          Social          |        200       |    24 < N < 27   |
146 | |    Planar-60    |       2D       |          Social          |        200       |      N = 60      |
147 | |    AIDS         |       2D       | Bioinformatics/Molecular |        2000      |         -        |
148 | |   Synthie       |       2D       |          Social          |        300       |      N = 100     |
149 | |    Proteins     |       3D       | Bioinformatics/Protein   |        1113      |      N = 39.1    |
150 | 
151 | ### Molecule generation
152 | 
153 | | Methods | Paper | Source | Methods | Paper | Source |
154 | | :----: | :----: | :----: | :----: | :----: | :----: |
155 | | Zinc | [[paper]](https://doi.org/10.1021/ci3001277) | [[source]](https://zinc.docking.org/) | GEOM-QM9 | [[paper]](https://doi.org/10.1038/sdata.2014.22) | [[source]](https://doi.org/10.7910/DVN/JNGTDF) |
156 | | GEOM-Drugs | [[paper]](https://doi.org/10.1038/s41597-022-01288-4) | [[source]](https://doi.org/10.7910/DVN/JNGTDF) | CrossDocked2020 | [[paper]](https://doi.org/10.1021/acs.jcim.0c00411) | [[source]](https://github.com/gnina/models) |
157 | | BioLiP | [[paper]](https://doi.org/10.1093/nar/gks966) | [[source]](https://zhanggroup.org/BioLiP/index.cgi) | PDBBind | [[paper]](https://doi.org/10.1021/acs.accounts.6b00491) | [[source]](http://www.pdbbind.org.cn/) |
158 | | SAbDab | [[paper]](https://doi.org/10.1093/nar/gkt1043) | [[source]](https://opig.stats.ox.ac.uk/webapps/sabdab-sabpred/sabdab) | - | - | - |
159 | ### Motion generation
160 | 
161 | | Methods | Paper | Source | Methods | Paper | Source |
162 | | :----: | :----: | :----: | :----: | :----: | :----: |
163 | | Human3.6M | [[paper]](https://doi.org/10.1109/TPAMI.2013.248) | [[source]](http://vision.imar.ro/human3.6m/description.php) | HumanEva-I | [[paper]](https://doi.org/10.1007/s11263-009-0273-6) | [[source]](http://humaneva.is.tue.mpg.de/) |
164 | | HumanAct12 | [[paper]](https://doi.org/10.1145/3394171.3413635) | [[source]](https://ericguo5513.github.io/action-to-motion/) | HumanML3D | [[paper]](https://openaccess.thecvf.com/content/CVPR2022/html/Guo_Generating_Diverse_and_Natural_3D_Human_Motions_From_Text_CVPR_2022_paper.html) | [[source]](https://github.com/EricGuo5513/HumanML3D) |
165 | | KIT | [[paper]](https://doi.org/10.1089/big.2016.0028) | [[source]](https://motion-annotation.humanoids.kit.edu/dataset/) | BABEL | [[paper]](https://openaccess.thecvf.com/content/CVPR2021/html/Punnakkal_BABEL_Bodies_Action_and_Behavior_With_English_Labels_CVPR_2021_paper.html) | [[source]](https://babel.is.tue.mpg.de/) |
166 | | UESTC | [[paper]](https://doi.org/10.1145/3240508.3240675) | [[source]](https://github.com/HRI-UESTC/CFM-HRI-RGB-D-action-database) | 3DPW | [[paper]](https://openaccess.thecvf.com/content_ECCV_2018/html/Timo_von_Marcard_Recovering_Accurate_3D_ECCV_2018_paper.html) | [[source]](http://virtualhumans.mpi-inf.mpg.de/3DPW) |
167 | | NTU RGB+D | [[paper]](https://openaccess.thecvf.com/content_cvpr_2016/html/Shahroudy_NTU_RGBD_A_CVPR_2016_paper.html) | [[source]](https://rose1.ntu.edu.sg/dataset/actionRecognition/) | AIST++ | [[paper]](https://openaccess.thecvf.com/content/ICCV2021/html/Li_AI_Choreographer_Music_Conditioned_3D_Dance_Generation_With_AIST_ICCV_2021_paper.html) | [[source]](https://google.github.io/aichoreographer) |
168 | | TSG | [[paper]](https://doi.org/10.1145/3267851.3267898) | [[source]]() | ZeroEGGS | [[paper]](https://doi.org/10.1111/cgf.14734) | [[source]](https://github.com/ubisoft/ubisoft-laforge-ZeroEGGS) |
169 | 
170 | ## Other surveys
171 | | Paper | Url | Source | 
172 | | :---- | :----: | :----: 
173 | | Diffusion-based Graph Generative Methods | [[paper]](https://arxiv.org/abs/2401.15617) | [[source]](https://github.com/zhejiangzhuque/Diffusion-based-Graph-Generative-Methods) |
174 | | Diffusion Models: A Comprehensive Survey of Methods and Applications | [[paper]](https://doi.org/10.48550/arXiv.2209.00796) | [[source]](https://github.com/YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy) |
175 | | A Survey on Generative Diffusion Model | [[paper]](https://doi.org/10.48550/arXiv.2209.02646) | [[source]](https://github.com/chq1155/A-Survey-on-Generative-Diffusion-Model) |
176 | | Generative Diffusion Models on Graphs: Methods and Applications | [[paper]](https://doi.org/10.48550/arXiv.2302.02591) | - |
177 | | A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material | [[paper]](https://rgdoi.net/10.13140/RG.2.2.26493.64480) | - |
178 | | Graph-based Molecular Representation Learning | [[paper]](https://doi.org/10.48550/arXiv.2207.04869) | - |
179 | | Generative Models as an Emerging Paradigm in the Chemical Sciences | [[paper]](https://doi.org/10.1021/jacs.2c13467) | - |
180 | | A Survey on Deep Graph Generation: Methods and Applications (LoG-22) | [[paper]](https://doi.org/10.48550/arXiv.2203.06714) | - |
181 | | A Survey on Temporal Graph Representation Learning and Generative Modeling | [[paper]](https://doi.org/10.48550/arXiv.2208.12126) | - |
182 | | Human motion modeling with deep learning: A survey | [[paper]](https://doi.org/10.1016/j.aiopen.2021.12.002) | - |
183 | | MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design | [[paper]](https://doi.org/10.48550/arXiv.2203.14500) | - |
184 | 
185 | ## Acknowledgement :heart:
186 | Thanks to [Diffusion-based-Graph-Generative-Methods](https://github.com/zhejiangzhuque/Diffusion-based-Graph-Generative-Methods).
187 | 
188 | ## Star History
189 | 
190 | [![Star History Chart](https://api.star-history.com/svg?repos=yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications&type=Date)](https://star-history.com/#yuntaoshou/Graph-Diffusion-Models-A-Comprehensive-Survey-of-Methods-and-Applications&Date)
191 | 


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