├── LICENSE └── README.md /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2023 Leo Xu 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Diffusion-based Grap Generative Methods 2 | This is the summation of all the methods, datasets, and other survey mentioned in our survey 'Diffusion-based Graph Generative Methods'. 3 | 4 | ## Contents 5 | - [Diffusion-based Grap Generative Methods](#diffusion-based-grap-generative-methods) 6 | - [Contents](#contents) 7 | - [Molecule generation](#molecule-generation) 8 | - [De novo molecule design](#de-novo-molecule-design) 9 | - [Conformation design](#conformation-design) 10 | - [De novo ligand design](#de-novo-ligand-design) 11 | - [Ligand docking](#ligand-docking) 12 | - [Protein design](#protein-design) 13 | - [Motion generation](#motion-generation) 14 | - [Motion synthesis](#motion-synthesis) 15 | - [Motion prediction](#motion-prediction) 16 | - [Others](#others) 17 | - [Datasets](#datasets) 18 | - [Molecule generation](#molecule-generation-1) 19 | - [Motion generation](#motion-generation-1) 20 | - [Other surveys](#other-surveys) 21 | 22 | 23 | ## Molecule generation 24 | 25 | ### De novo molecule design 26 | | Methods | Paper | Code | Methods | Paper | Code | 27 | | :----: | :----: | :----: | :----: | :----: | :----: | 28 | | 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) | 29 | | 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) | 30 | | 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) | - | 31 | | 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) | 32 | | 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) | - | 33 | | HierDiff (ICML-23) | [[paper]](https://proceedings.mlr.press/v202/qiang23a.html) | [[code]](https://github.com/qiangbo1222/HierDiff) | GeoLDM (ICML-23) | [[papar]](https://proceedings.mlr.press/v202/xu23n.html) | [[code]](https://github.com/MinkaiXu/GeoLDM) | 34 | | DiffMol (ICML-23) | [[paper]](https://openreview.net/forum?id=x43ZyXJC9q) | - | - | - | - | 35 | 36 | ### Conformation design 37 | | Methods | Paper | Code | Methods | Paper | Code | 38 | | :----: | :----: | :----: | :----: | :----: | :----: | 39 | | 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) | - | 40 | | 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) | - | 41 | | 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) | - | 42 | | RINGER| [[paper]](https://doi.org/10.48550/arXiv.2305.19800) | - | - | - | - | 43 | ### De novo ligand design 44 | | Methods | Paper | Code | Methods | Paper | Code | 45 | | :----: | :----: | :----: | :----: | :----: | :----: | 46 | | DiffBP | [[paper]](https://arxiv.org/abs/2211.11214) | - | DiffSBDD | [[paper]](https://arxiv.org/abs/2210.13695) | - | 47 | | 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) | - | 48 | | D3FG | [[paper]](https://doi.org/10.48550/arXiv.2306.13769) | - | - | - | - | 49 | ### Ligand docking 50 | | Methods | Paper | Code | 51 | | :----: | :----: | :----: | 52 | | DIFFDOCK (NeurIPS-22) | [[paper]](https://openreview.net/forum?id=fky3a3F80if) | - | 53 | | EDM-Dock (JCIM) | [[paper]](https://doi.org/10.1021/acs.jcim.2c01436) | [[code]](https://github.com/MatthewMasters/EDM-Dock) | 54 | | DPL | [[paper]](https://doi.org/10.1186/s12859-023-05354-5) | [[code]](https://github.com/shuyana/DiffusionProteinLigand) | 55 | | NeuralPLexer | [[paper]](https://doi.org/10.48550/arXiv.2209.15171) | - | 56 | ### Protein design 57 | | Methods | Paper | Code | Methods | Paper | Code | 58 | | :----: | :----: | :----: | :----: | :----: | :----: | 59 | | DiffAb (NeurIPS-22) | [[paper]](https://openreview.net/forum?id=jSorGn2Tjg) | - | Anand | [[paper]](https://arxiv.org/abs/2205.15019) | - | 60 | | 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) | 61 | | 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) | - | 62 | | EigenFold | [[paper]](https://openreview.net/forum?id=BgbRVzfQqFp) | [[code]](https://github.com/bjing2016/EigenFold) | - | - | - | 63 | ## Motion generation 64 | 65 | ### Motion synthesis 66 | | Methods | Paper | Code | Homepage | Methods | Paper | Code | Homepage | 67 | | :----: | :----: | :----: | :----: | :----: | :----: | :----: | :----: | 68 | | 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) | - | - | 69 | | Ren et al. (ICASSP-23) | [[paper]](https://doi.org/10.1109/ICASSP49357.2023.10096441) | - | - | FLAME (AAAI-23) | [[paper]](https://arxiv.org/abs/2209.00349) | - | - | 70 | | 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/) | 71 | | 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/) | 72 | | 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/) | 73 | | 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) | 74 | | BiGraphDiff | [[paper]](https://arxiv.org/abs/2301.10134) | - | - | DiffuPose | [[paper]](https://doi.org/10.48550/arXiv.2212.02796) | - | - | 75 | 77 | ### Motion prediction 78 | | Methods | Paper | Code | Homepage | 79 | | :----: | :----: | :----: | :----: | 80 | | 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) | 81 | | HumanMAC | [[paper]](https://arxiv.org/abs/2302.03665) | [[code]](https://github.com/LinghaoChan/HumanMAC) | [[homepage]](https://lhchen.top/Human-MAC/) | 82 | | TCD (ICRA-23) | [[paper]](https://doi.org/10.1109/ICRA48891.2023.10160399) | [[code]](https://github.com/vita-epfl/DePOSit) | - | 83 | | DiffMotion | [[paper]](https://doi.org/10.48550/arXiv.2305.12554) | - | - | 84 | 85 | ## Others 86 | | Methods | Paper | Code | Homepage | Methods | Paper | Code | Homepage | 87 | | :----: | :----: | :----: | :----: | :----: | :----: | :----: | :----: | 88 | | EDP-GNN | [[paper]](https://proceedings.mlr.press/v108/niu20a.html) | - | - | GSDM | [[paper]](https://arxiv.org/abs/2211.08892) | - | - | 89 | | NVDiff | [[paper]](https://arxiv.org/abs/2211.10794) | - | - | DPM-GSP | [[paper]](https://arxiv.org/abs/2302.10506) | - | - | 90 | | DiffSTG | [[paper]](https://arxiv.org/abs/2301.13629) | - | - | DIFUSCO | [[paper]](https://arxiv.org/abs/2302.08224) | - | - | 91 | | 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/) | 92 | | NAP | [[paper]](https://arxiv.org/abs/2305.16315) | - | [[homepage]](https://www.cis.upenn.edu/~leijh/projects/nap/) | EDGE (ICML-23) | [[paper]](https://openreview.net/forum?id=vn9O1N5ZOw) | - | - | 93 | | DruM | [[paper]](https://arxiv.org/abs/2302.03596) | - | - | DDM | [[Paper]](https://arxiv.org/abs/2306.13210) | - | - | 94 | | DiffusionNAG | [[paper]](https://arxiv.org/abs/2305.16943) | - | - | TSDiff | [[paper]](https://doi.org/10.21203/rs.3.rs-2924237/v1) | - | - | 95 | | GraphArm (ICML-23) | [[paper]](https://proceedings.mlr.press/v202/kong23b.html) | - | - | HGDM | [[paper]](https://doi.org/10.48550/arXiv.2306.07618) | [[code]](https://github.com/GRAPH-0/JODO) | - | 96 | | Lee et al. | [[paper]](https://doi.org/10.1080/15376494.2023.2198528) | - | - | SaGess | [[paper]](https://doi.org/10.48550/arXiv.2306.16827) | - | - | 97 | | SLD | [[paepr]](https://openreview.net/forum?id=AykEgQNPJEK) | - | - | Diff-POI | [[paper]](https://doi.org/10.48550/arXiv.2304.07041) | - | - | 98 | | Brain Diffuser | [[paper]](https://doi.org/10.48550/arXiv.2303.06410) | - | - | Lu et al. | [[paper]](https://doi.org/10.48550/arXiv.2304.05137) | - | - | 99 | 100 | ## Datasets 101 | 102 | ### Molecule generation 103 | 104 | | Methods | Paper | Source | Methods | Paper | Source | 105 | | :----: | :----: | :----: | :----: | :----: | :----: | 106 | | 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) | 107 | | 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) | 108 | | 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/) | 109 | | SAbDab | [[paper]](https://doi.org/10.1093/nar/gkt1043) | [[source]](https://opig.stats.ox.ac.uk/webapps/sabdab-sabpred/sabdab) | - | - | - | 110 | ### Motion generation 111 | 112 | | Methods | Paper | Source | Methods | Paper | Source | 113 | | :----: | :----: | :----: | :----: | :----: | :----: | 114 | | 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/) | 115 | | 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) | 116 | | 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/) | 117 | | 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) | 118 | | 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) | 119 | | 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) | 120 | 121 | ## Other surveys 122 | | Paper | Url | Source | 123 | | :---- | :----: | :----: | 124 | | 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) | 125 | | 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) | 126 | | Generative Diffusion Models on Graphs: Methods and Applications | [[paper]](https://doi.org/10.48550/arXiv.2302.02591) | - | 127 | | 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) | - | 128 | | Graph-based Molecular Representation Learning | [[paper]](https://doi.org/10.48550/arXiv.2207.04869) | - | 129 | | Generative Models as an Emerging Paradigm in the Chemical Sciences | [[paper]](https://doi.org/10.1021/jacs.2c13467) | - | 130 | | A Survey on Deep Graph Generation: Methods and Applications (LoG-22) | [[paper]](https://doi.org/10.48550/arXiv.2203.06714) | - | 131 | | A Survey on Temporal Graph Representation Learning and Generative Modeling | [[paper]](https://doi.org/10.48550/arXiv.2208.12126) | - | 132 | | Human motion modeling with deep learning: A survey | [[paper]](https://doi.org/10.1016/j.aiopen.2021.12.002) | - | 133 | | MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design | [[paper]](https://doi.org/10.48550/arXiv.2203.14500) | - | --------------------------------------------------------------------------------