Organize the current research on graph diffusion generation.
- A curated list of up-to-date graph diffusion generation papers and resources.
- This Repo is being actively updated and maintained! 03/21/24
- Please let us know if we miss any papers!
Generative Diffusion Models on Graphs: Methods and Applications IJCAI 2023
Sparse Training of Discrete Diffusion Models for Graph Generation Arxiv 2024 Autoregressive Diffusion Model for Graph Generation ICML 2023 Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling ICML 2023 DiGress: Discrete Denoising diffusion for graph generation ICLR 2023 Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation AAAI 2023 GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation ICDM 2022
Permutation Invariant Graph Generation via Score-Based Generative Modeling Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon AISTATS 2021. [Paper] [Github] 2 Mar 2020
Learning gradient fields for molecular conformation generation Chence Shi, Shitong Luo, Minkai Xu, Jian Tang ICML 2021. [Paper] [Github] 9 May 2021
Diffusion Models for Graphs Benefit From Discrete State Spaces Kilian Konstantin Haefeli, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer LoG 2022 and NeurIPS GLFrontiers 2022. [Paper] [Github] 4 Oct 2022
DiGress: Discrete Denoising diffusion for graph generation Clement Vignac1, Igor Krawczuk1, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard ICLR 2023. [Paper] [Github] 29 Sep 2022
GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation Han Huang, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv IEEE ICDM 2022. [Paper] [Github] 4 Dec 2022
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations Jaehyeong Jo, Seul Lee, Sung Ju Hwang ICML, 2022. [Paper] [Github] 5 Feb 2022
Fast Graph Generative Model via Spectral Diffusion Tianze Luo, Zhanfeng Mo, Sinno Jialin Pan arXiv 2022. [Paper] 16 Nov 2022
Score-based graph generative modeling with self-guided latent diffusion Ling Yang, Zhilong Zhang, Wentao Zhang, and Shenda Hong OpenReview. [Paper] 02 Feb 2023
Geometric Latent Diffusion Models for 3D Molecule Generation ICML 2023 Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D ICML 2023 Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation Arxiv 2023 MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation Arxiv 2023
MDM: Molecular Diffusion Model for 3D Molecule Generation Lei Huang, Hengtong Zhang, Tingyang Xu, Ka-Chun Wong Submitted to AAAI'23. [Paper] 13 Sep 2022
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang ICLR 2022. [Paper] [Github] 6 Mar 2022
Equivariant Diffusion for Molecule Generation in 3D Emiel Hoogeboom, Vıctor Garcia Satorras, Clement Vignac, and Max Welling ICML 2022. [Paper] [Github] 31 Mar 2022
Equivariant Energy-Guided SDE for Inverse Molecular Design Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu ICLR 2023. [Paper] [Github] 30 Sep 2022
Predicting Molecular Conformation via Dynamic Graph Score Matching Shitong Luo, Chence Shi, Minkai Xu, Jian Tang NeurIPS 2021. [Paper] 22 May 2021
Torsional Diffusion for Molecular Conformer Generation Bowen Jing, Gabriele Corso, Regina Barzilay, Tommi S. Jaakkola NeurIPS 2022. [Paper] [Github] 1 Jun 2022
Exploring Chemical Space with Score-based Out-of-distribution Generation Seul Lee, Jaehyeong Jo, Sung Ju Hwang ICML 2023. [Paper] [Github] 6 Jun 2022
Diffusion-based Molecule Generation with Informative Prior Bridges Lemeng Wu1, Chengyue Gong1, Xingchao Liu, Mao Ye, Qiang Liu NeurIPS 2022. [Paper] 2 Sep 2022
Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design Ilia Igashov, Hannes Stärk, Clément Vignac, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael Bronstein, Bruno Correia NeurIPS 2022. [Paper] [Github] 11 Oct 2022
DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding Haitao Lin1, Yufei Huang1, Meng Liu, Xuanjing Li, Shuiwang Ji, Stan Z. Li arXiv 2022. [Paper] 21 Nov 2022
Pocket-specific 3D Molecule Generation by Fragment-based Autoregressive Diffusion Models Xingang Peng, Jiaqi Guan, Jian Peng, Jianzhu Ma OpenReview 2022. [Paper] 02 Feb 2023
3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction Jiaqi Guan, Wesley Wei Qian, Xingang Peng, Yufeng Su, Jian Peng, Jianzhu Ma ICLR 2023. [Paper] [Github] 6 Mar 2023
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi Jaakkola ICLR 2023. [Paper] [Github] 4 Oct 2022
Protein Representation Learning by Geometric Structure Pretraining Zuobai Zhang, Minghao Xu, Arian Jamasb, Vijil Chenthamarakshan, Aurelie Lozano, Payel Das, Jian Tang arXiv 2022.. [Paper] [Github] 11 Mar 2022
Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models Namrata Anand, Tudor Achim arXiv 2022. [Paper] [Project] [Github] 26 May 2022
Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem Brian L. Trippe1, Jason Yim1, Doug Tischer, Tamara Broderick, David Baker, Regina Barzilay, Tommi Jaakkola ICLR 2023. [Paper] [Github] 8 Jun 2022
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models Shitong Luo1, Yufeng Su1, Xingang Peng, Sheng Wang, Jian Peng, Jianzhu Ma NeurIPS 2022. [Paper] 11 Jul 2022
Protein structure generation via folding diffusion Kevin E. Wu, Kevin K. Yang, Rianne van den Berg, James Y. Zou, Alex X. Lu, Ava P. Amini arXiv 2022. [Paper] [Github] 30 Sep 2022
Score-based generative modeling for de novo protein design Jin Sub Lee, Jisun Kim & Philip M. Kim Nature Computational Science 2023. [Paper] [Github] 04 May 2023
Protein-ligand Complex Structure Predictiong DDPM End-to-end protein–ligand complex structure generation with diffusion-based generative models Shuya Nakata, Yoshiharu Mori, and Shigenori Tanaka BMC Bioinformatics 2023. [Paper] 22 December 2022
Dynamic-backbone protein-ligand structure prediction with multiscale generative diffusion models tate-specific protein-ligand complex structure prediction with a multi-scale deep generative model (new version) Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F Miller III, and Anima Anandkumar NeurIPS 2022. [Paper] 22 December 2022
Protein Design with Guided Discrete Diffusion NeurIPS 2023
Thanks this works： @article{fan2023generative, title={Generative diffusion models on graphs: Methods and applications}, author={Fan, Wenqi and Liu, Chengyi and Liu, Yunqing and Li, Jiatong and Li, Hang and Liu, Hui and Tang, Jiliang and Li, Qing}, journal={arXiv preprint arXiv:2302.02591}, year={2023} }