1. SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation
    Qi Yan, Zhengyang Liang, Yang Song, Renjie Liao, Lele Wang
    arXiv 2023. Paper   Github  
    2023-07-04
    2023-07-04
  2. Graph Denoising Diffusion for Inverse Protein Folding
    Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Liò, Yu Guang Wang
    arXiv 2023. Paper  
    2023-06-29
    2023-06-29
  3. SaGess: Sampling Graph Denoising Diffusion Model for Scalable Graph Generation
    Stratis Limnios, Praveen Selvaraj, Mihai Cucuringu, Carsten Maple, Gesine Reinert, Andrew Elliott
    arXiv 2023. Paper  
    2023-06-29
    2023-06-29
  4. DiffDTM: A conditional structure-free framework for bioactive molecules generation targeted for dual proteins
    Lei Huang, Zheng Yuan, Huihui Yan, Rong Sheng, Linjing Liu, Fuzhou Wang, Weidun Xie, Nanjun Chen, Fei Huang, Songfang Huang, Ka-Chun Wong, Yaoyun Zhang
    arXiv 2023. Paper  
    2023-06-24
    2023-06-24
  5. Hyperbolic Graph Diffusion Model for Molecule Generation
    Lingfeng Wen, Xian Wei
    arXiv 2023. Paper  
    2023-06-13
    2023-06-13
  6. 3D molecule generation by denoising voxel grids
    Pedro O. Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, Omar Mahmood, Andrew Martin Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi
    arXiv 2023. Paper  
    2023-06-13
    2023-06-13
  7. Complexity-aware Large Scale Origin-Destination Network Generation via Diffusion Model
    Can Rong, Jingtao Ding, Zhicheng Liu, Yong Li
    arXiv 2023. Paper  
    2023-06-08
    2023-06-08
  8. DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing
    Yangtian Zhan, Zuobai Zhang, Bozitao Zhong, Sanchit Misra, Jian Tang
    arXiv 2023. Paper  
    2023-06-01
    2023-06-01
  9. Protein Design with Guided Discrete Diffusion
    Nate Gruver, Samuel Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hotzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson
    arXiv 2023. Paper  
    2023-05-31
    2023-05-31
  10. RINGER: Rapid Conformer Generation for Macrocycles with Sequence-Conditioned Internal Coordinate Diffusion
    Colin A. Grambow, Hayley Weir, Nathaniel L. Diamant, Alex M. Tseng, Tommaso Biancalani, Gabriele Scalia, Kangway V. Chuang
    arXiv 2023. Paper  
    2023-05-30
    2023-05-30
  11. A Diffusion Model for Event Skeleton Generation
    Fangqi Zhu, Lin Zhang, Jun Gao, Bing Qin, Ruifeng Xu, Haiqin Yang
    arXiv 2023. Paper   Github  
    2023-05-27
    2023-05-27
  12. Confidence-Based Feature Imputation for Graphs with Partially Known Features
    Daeho Um, Jiwoong Park, Seulki Park, Jin Young Choi
    ICLR 2023. Paper   Github  
    2023-05-26
    2023-05-26
  13. Trans-Dimensional Generative Modeling via Jump Diffusion Models
    Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Tom Rainforth, Arnaud Doucet
    arXiv 2023. Paper  
    2023-05-25
    2023-05-25
  14. Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation
    Han Huang, Leilei Sun, Bowen Du, Weifeng Lv
    arXiv 2023. Paper   Github  
    2023-05-21
    2023-05-21
  15. Spatio-temporal Diffusion Point Processes
    Yuan Yuan, Jingtao Ding, Chenyang Shao, Depeng Jin, Yong Li
    arXiv 2023. Paper   Github  
    2023-05-21
    2023-05-21
  16. MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation
    Xingang Peng, Jiaqi Guan, Qiang Liu, Jianzhu Ma
    ICML 2023. Paper  
    2023-05-11
    2023-05-11
  17. A Latent Diffusion Model for Protein Structure Generation
    Cong Fu, Keqiang Yan, Limei Wang, Wing Yee Au, Michael McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji
    arXiv 2023. Paper  
    2023-05-06
    2023-05-06
  18. Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling
    Xiaohui Chen, Jiaxing He, Xu Han, Li-Ping Liu
    ICML 2023. Paper  
    2023-05-06
    2023-05-06
  19. Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D
    Bo Qiang, Yuxuan Song, Minkai Xu, Jingjing Gong, Bowen Gao, Hao Zhou, Weiying Ma, Yanyan Lan
    arXiv 2023. Paper  
    2023-05-05
    2023-05-05
  20. Geometric Latent Diffusion Models for 3D Molecule Generation
    Minkai Xu, Alexander Powers, Ron Dror, Stefano Ermon, Jure Leskovec
    ICML 2023. Paper  
    2023-05-02
    2023-05-02
  21. MUDiff: Unified Diffusion for Complete Molecule Generation
    Chenqing Hua, Sitao Luan, Minkai Xu, Rex Ying, Jie Fu, Stefano Ermon, Doina Precup
    arXiv 2023. Paper  
    2023-04-28
    2023-04-28
  22. A 2D Graph-Based Generative Approach For Exploring Transition States Using Diffusion Model
    Seonghwan Kim, Jeheon Woo, Woo Youn Kim
    arXiv 2023. Paper  
    2023-04-20
    2023-04-20
  23. Two-stage Denoising Diffusion Model for Source Localization in Graph Inverse Problems
    Bosong Huang, Weihao Yu, Ruzhong Xie, Jing Xiao, Jin Huang
    arXiv 2023. Paper  
    2023-04-18
    2023-04-18
  24. Towards Controllable Diffusion Models via Reward-Guided Exploration
    Hengtong Zhang, Tingyang Xu
    arXiv 2023. Paper  
    2023-04-14
    2023-04-14
  25. Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model
    Chenru Duan, Yuanqi Du, Haojun Jia, Heather J. Kulik
    arXiv 2023. Paper  
    2023-04-12
    2023-04-12
  26. DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models
    Mohamed Amine Ketata, Cedrik Laue, Ruslan Mammadov, Hannes Stärk, Menghua Wu, Gabriele Corso, Céline Marquet, Regina Barzilay, Tommi S. Jaakkola
    ICLR 2023. Paper  
    2023-04-08
    2023-04-08
  27. EigenFold: Generative Protein Structure Prediction with Diffusion Models
    Bowen Jing, Ezra Erives, Peter Pao-Huang, Gabriele Corso, Bonnie Berger, Tommi Jaakkola
    ICLR Workshop 2023. Paper   Github  
    2023-04-05
    2023-04-05
  28. 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  
    2023-03-06
    2023-03-06
  29. Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties
    Nikolaos N. Vlassis, WaiChing Sun
    arXiv 2023. Paper  
    2023-02-24
    2023-02-24
  30. Aligned Diffusion Schrödinger Bridges
    Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, Maria Rodriguez Martinez, Andreas Krause, Charlotte Bunne
    arXiv 2023. Paper  
    2023-02-22
    2023-02-22
  31. Diffusion Probabilistic Models for Graph-Structured Prediction
    Hyosoon Jang, Sangwoo Mo, Sungsoo Ahn
    arXiv 2023. Paper  
    2023-02-21
    2023-02-21
  32. MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation
    Clement Vignac, Nagham Osman, Laura Toni, Pascal Frossard
    arXiv 2023. Paper  
    2023-02-17
    2023-02-17
  33. Geometry-Complete Diffusion for 3D Molecule Generation
    Alex Morehead, Jianlin Cheng
    ICML Workshop 2023. Paper   Github  
    2023-02-08
    2023-02-08
  34. GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusion
    Alex M. Tseng, Nathaniel Diamant, Tommaso Biancalani, Gabriele Scalia
    arXiv 2023. Paper  
    2023-02-07
    2023-02-07
  35. Graph Generation with Destination-Driven Diffusion Mixture
    Jaehyeong Jo, Dongki Kim, Sung Ju Hwang
    arXiv 2023. Paper  
    2023-02-07
    2023-02-07
  36. SE(3) diffusion model with application to protein backbone generation
    Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi Jaakkola
    arXiv 2023. Paper  
    2023-02-05
    2023-02-05
  37. Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy
    Yufei Huang, Lirong Wu, Haitao Lin, Jiangbin Zheng, Ge Wang, Stan Z. Li
    arXiv 2023. Paper  
    2023-02-05
    2023-02-05
  38. Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics
    Marloes Arts, Victor Garcia Satorras, Chin-Wei Huang, Daniel Zuegner, Marco Federici, Cecilia Clementi, Frank Noé, Robert Pinsler, Rianne van den Berg
    arXiv 2023. Paper  
    2023-02-01
    2023-02-01
  39. DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models
    Haomin Wen, Youfang Lin, Yutong Xia, Huaiyu Wan, Roger Zimmermann, Yuxuan Liang
    arXiv 2023. Paper  
    2023-01-31
    2023-01-31
  40. Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds
    Yeqing Lin, Mohammed AlQuraishi
    arXiv 2023. Paper  
    2023-01-29
    2023-01-29
  41. Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction
    Zuobai Zhang, Minghao Xu, Aurélie Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
    arXiv 2023. Paper  
    2023-01-28
    2023-01-28
  42. DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
    Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan
    ICLR 2023. Paper  
    2023-01-23
    2023-01-23
  43. DiffSDS: A language diffusion model for protein backbone inpainting under geometric conditions and constraints
    Zhangyang Gao, Cheng Tan, Stan Z. Li
    arXiv 2023. Paper  
    2023-01-22
    2023-01-22
  44. GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation
    Han Huang, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv
    IEEE ICDM 2022. Paper   Github  
    2022-12-04
    2022-12-04
  45. DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding
    Haitao Lin, Yufei Huang, Meng Liu, Xuanjing Li, Shuiwang Ji, Stan Z. Li
    arXiv 2022. Paper  
    2022-11-21
    2022-11-21
  46. NVDiff: Graph Generation through the Diffusion of Node Vectors
    Cristian Sbrolli, Paolo Cudrano, Matteo Frosi, Matteo Matteucci
    arXiv 2022. Paper  
    2022-11-20
    2022-11-20
  47. Fast Graph Generative Model via Spectral Diffusion
    Tianze Luo, Zhanfeng Mo, Sinno Jialin Pan
    arXiv 2022. Paper  
    2022-11-16
    2022-11-16
  48. ParticleGrid: Enabling Deep Learning using 3D Representation of Materials
    Shehtab Zaman, Ethan Ferguson, Cecile Pereira, Denis Akhiyarov, Mauricio Araya-Polo, Kenneth Chiu
    IEEE eScience 2022. Paper  
    2022-11-15
    2022-11-15
  49. Structure-based Drug Design with Equivariant Diffusion Models
    Arne Schneuing, Yuanqi Du, Charles Harris, Arian Jamasb, Ilia Igashov, Weitao Du, Tom Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael Bronstein, Bruno Correia
    arXiv 2022. Paper  
    2022-10-24
    2022-10-24
  50. Protein Sequence and Structure Co-Design with Equivariant Translation
    Chence Shi, Chuanrui Wang, Jiarui Lu, Bozitao Zhong, Jian Tang
    ICLR 2023. Paper  
    2022-10-17
    2022-10-17
  51. 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
    arXiv 2022. Paper  
    2022-10-11
    2022-10-11
  52. Diffusion Models for Graphs Benefit From Discrete State Spaces
    Kilian Konstantin Haefeli, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer
    NeurIPS Workshop 2022. Paper  
    2022-10-04
    2022-10-04
  53. State-specific protein-ligand complex structure prediction with a multi-scale deep generative model
    Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Anima Anandkumar
    NeurIPS Workshop 2022. Paper  
    2022-09-30
    2022-09-30
  54. Equivariant Energy-Guided SDE for Inverse Molecular Design
    Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu
    ICLR 2023. Paper  
    2022-09-30
    2022-09-30
  55. 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  
    2022-09-30
    2022-09-30
  56. DiGress: Discrete Denoising diffusion for graph generation
    Clement Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard
    ICLR 2023. Paper  
    2022-09-29
    2022-09-29
  57. MDM: Molecular Diffusion Model for 3D Molecule Generation
    Lei Huang, Hengtong Zhang, Tingyang Xu, Ka-Chun Wong
    AAAI 2023. Paper  
    2022-09-13
    2022-09-13
  58. Diffusion-based Molecule Generation with Informative Prior Bridges
    Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu
    NeurIPS 2022. Paper  
    2022-09-02
    2022-09-02
  59. Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models
    Shitong Luo, Yufeng Su, Xingang Peng, Sheng Wang, Jian Peng, Jianzhu Ma
    BioRXiv 2022. Paper  
    2022-07-11
    2022-07-11
  60. Data-driven discovery of novel 2D materials by deep generative models
    Peder Lyngby, Kristian Sommer Thygesen
    NPJ 2022. Paper  
    2022-06-24
    2022-06-24
  61. Score-based Generative Models for Calorimeter Shower Simulation
    Vinicius Mikuni, Benjamin Nachman
    arXiv 2022. Paper  
    2022-06-17
    2022-06-17
  62. Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem
    Brian L. Trippe, Jason Yim, Doug Tischer, Tamara Broderick, David Baker, Regina Barzilay, Tommi Jaakkola
    CoRR 2022. Paper  
    2022-06-08
    2022-06-08
  63. Torsional Diffusion for Molecular Conformer Generation
    Bowen Jing, Gabriele Corso, Regina Barzilay, Tommi S. Jaakkola
    ICLR Workshop 2022. Paper   Github  
    2022-06-01
    2022-06-01
  64. Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models
    Namrata Anand, Tudor Achim
    arXiv 2022. Paper   Project   Github  
    2022-05-26
    2022-05-26
  65. A Score-based Geometric Model for Molecular Dynamics Simulations
    Fang Wu, Qiang Zhang, Xurui Jin, Yinghui Jiang, Stan Z. Li
    CoRR 2022. Paper  
    2022-04-19
    2022-04-19
  66. Equivariant Diffusion for Molecule Generation in 3D
    Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling
    ICML 2022. Paper   Github  
    2022-03-31
    2022-03-31
  67. 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  
    2022-03-06
    2022-03-06
  68. Crystal Diffusion Variational Autoencoder for Periodic Material Generation
    Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi Jaakkol
    NeurIPS 2021. Paper   Github  
    2021-10-12
    2021-10-12
  69. Predicting Molecular Conformation via Dynamic Graph Score Matching
    Shitong Luo, Chence Shi, Minkai Xu, Jian Tang
    NeurIPS 2021. Paper  
    2021-05-22
    2021-05-22
  70. 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  
    2020-03-02
    2020-03-02
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