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GraphDF: A Discrete Flow Model for Molecular Graph Generation
v1v2 (latest)

GraphDF: A Discrete Flow Model for Molecular Graph Generation

International Conference on Machine Learning (ICML), 2021
1 February 2021
Youzhi Luo
Keqiang Yan
Shuiwang Ji
    DRL
ArXiv (abs)PDFHTML

Papers citing "GraphDF: A Discrete Flow Model for Molecular Graph Generation"

50 / 139 papers shown
Saturn: Sample-efficient Generative Molecular Design using Memory
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Saturn: Sample-efficient Generative Molecular Design using Memory Manipulation
Jeff Guo
Philippe Schwaller
Mamba
249
12
0
27 May 2024
Regressor-free Molecule Generation to Support Drug Response Prediction
Regressor-free Molecule Generation to Support Drug Response Prediction
Kun Li
Xiuwen Gong
Shirui Pan
Hongzhi Zhang
Bo Du
Wenbin Hu
144
1
0
23 May 2024
Score-based Generative Models with Adaptive Momentum
Score-based Generative Models with Adaptive Momentum
Ziqing Wen
Xiaoge Deng
Ping Luo
Tao Sun
Dongsheng Li
DiffM
208
2
0
22 May 2024
Generated Contents Enrichment
Generated Contents Enrichment
Mahdi Naseri
Jiayan Qiu
Zhou Wang
341
0
0
06 May 2024
Data-Efficient Molecular Generation with Hierarchical Textual Inversion
Data-Efficient Molecular Generation with Hierarchical Textual InversionInternational Conference on Machine Learning (ICML), 2024
Seojin Kim
Jaehyun Nam
Sihyun Yu
Younghoon Shin
Jinwoo Shin
363
6
0
05 May 2024
GP-MoLFormer: A Foundation Model For Molecular Generation
GP-MoLFormer: A Foundation Model For Molecular GenerationDigital Discovery (DD), 2024
Jerret Ross
Brian M. Belgodere
Samuel C. Hoffman
Vijil Chenthamarakshan
Youssef Mroueh
Payel Das
Payel Das
300
16
0
04 Apr 2024
Molecular Generative Adversarial Network with Multi-Property Optimization
Molecular Generative Adversarial Network with Multi-Property Optimization
Huidong Tang
Chen Li
Sayaka Kamei
Yoshihiro Yamanishi
Yasuhiko Morimoto
304
1
0
29 Mar 2024
GLAD: Improving Latent Graph Generative Modeling with Simple
  Quantization
GLAD: Improving Latent Graph Generative Modeling with Simple Quantization
Van Khoa Nguyen
Yoann Boget
Frantzeska Lavda
Alexandros Kalousis
329
5
0
25 Mar 2024
Exploring the Potential of Large Language Models in Graph Generation
Exploring the Potential of Large Language Models in Graph Generation
Yang Yao
Xin Eric Wang
Zeyang Zhang
Yi Qin
Ziwei Zhang
Xu Chu
Yuekui Yang
Wenwu Zhu
Hong-yan Mei
259
21
0
21 Mar 2024
Complete and Efficient Graph Transformers for Crystal Material Property
  Prediction
Complete and Efficient Graph Transformers for Crystal Material Property PredictionInternational Conference on Learning Representations (ICLR), 2024
Keqiang Yan
Cong Fu
Xiaofeng Qian
Xiaoning Qian
Shuiwang Ji
335
38
0
18 Mar 2024
3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of
  Molecular Graphs
3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of Molecular Graphs
Huaisheng Zhu
Teng Xiao
V. Honavar
DiffM
177
5
0
11 Mar 2024
GraphRCG: Self-Conditioned Graph Generation
GraphRCG: Self-Conditioned Graph Generation
Song Wang
Zhen Tan
Xinyu Zhao
Tianlong Chen
Huan Liu
Wenlin Yao
200
0
0
02 Mar 2024
Graph Diffusion Policy Optimization
Graph Diffusion Policy Optimization
Yijing Liu
Chao Du
Tianyu Pang
Chongxuan Li
Wei Chen
Min Lin
252
14
0
26 Feb 2024
A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
A Graph is Worth KKK Words: Euclideanizing Graph using Pure Transformer
Zhangyang Gao
Daize Dong
Cheng Tan
Jun Xia
Bozhen Hu
Stan Z. Li
303
8
0
04 Feb 2024
Position: Graph Foundation Models are Already Here
Position: Graph Foundation Models are Already Here
Haitao Mao
Zhikai Chen
Wenzhuo Tang
Jianan Zhao
Yao Ma
Tong Zhao
Neil Shah
Mikhail Galkin
Shucheng Zhou
AI4CE
372
71
0
03 Feb 2024
Data Augmentation for Supervised Graph Outlier Detection with Latent
  Diffusion Models
Data Augmentation for Supervised Graph Outlier Detection with Latent Diffusion ModelsLOG IN (LOG IN), 2023
Kay Liu
Hengrui Zhang
Ziqing Hu
Fangxin Wang
Philip S. Yu
337
3
0
29 Dec 2023
Vector Field Oriented Diffusion Model for Crystal Material Generation
Vector Field Oriented Diffusion Model for Crystal Material Generation
Astrid Klipfel
Yael Fregier
A. Sayede
Zied Bouraoui
DiffM
148
12
0
20 Dec 2023
A Simple and Scalable Representation for Graph Generation
A Simple and Scalable Representation for Graph GenerationInternational Conference on Learning Representations (ICLR), 2023
Yunhui Jang
Seul Lee
SungSoo Ahn
251
10
0
04 Dec 2023
Genetic algorithms are strong baselines for molecule generation
Genetic algorithms are strong baselines for molecule generation
Austin Tripp
José Miguel Hernández-Lobato
174
33
0
13 Oct 2023
Kernel-Elastic Autoencoder for Molecular Design
Kernel-Elastic Autoencoder for Molecular DesignPNAS Nexus (PNAS Nexus), 2023
Haote Li
Yu Shee
B. Allen
F. Maschietto
Victor S. Batista
341
6
0
12 Oct 2023
Data-centric Graph Learning: A Survey
Data-centric Graph Learning: A SurveyIEEE Transactions on Big Data (IEEE Trans. Big Data), 2023
Jixi Liu
Deyu Bo
Cheng Yang
Haoran Dai
Qi Zhang
Yixin Xiao
Yufei Peng
Chuan Shi
GNN
331
29
0
08 Oct 2023
Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel
  Approach to Generating Molecules with Desirable Properties
Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel Approach to Generating Molecules with Desirable PropertiesIEEE/ACM Transactions on Computational Biology & Bioinformatics (TCBB), 2023
Siyuan Guo
Jihong Guan
Shuigeng Zhou
215
8
0
05 Oct 2023
Molecule Design by Latent Prompt Transformer
Molecule Design by Latent Prompt Transformer
Deqian Kong
Yuhao Huang
Jianwen Xie
Ying Nian Wu
337
6
0
05 Oct 2023
Drug Discovery with Dynamic Goal-aware Fragments
Drug Discovery with Dynamic Goal-aware FragmentsInternational Conference on Machine Learning (ICML), 2023
Seul Lee
Seanie Lee
Kenji Kawaguchi
Sung Ju Hwang
375
16
0
02 Oct 2023
Target-aware Variational Auto-encoders for Ligand Generation with
  Multimodal Protein Representation Learning
Target-aware Variational Auto-encoders for Ligand Generation with Multimodal Protein Representation LearningbioRxiv (bioRxiv), 2023
Haoxiang Luo
Gang Sun
203
2
0
02 Aug 2023
Autoregressive Diffusion Model for Graph Generation
Autoregressive Diffusion Model for Graph GenerationInternational Conference on Machine Learning (ICML), 2023
Lingkai Kong
Jiaming Cui
Haotian Sun
Yuchen Zhuang
B. Prakash
Chao Zhang
DiffM
158
89
0
17 Jul 2023
Towards Symmetry-Aware Generation of Periodic Materials
Towards Symmetry-Aware Generation of Periodic MaterialsNeural Information Processing Systems (NeurIPS), 2023
Youzhi Luo
Chengkai Liu
Shuiwang Ji
DiffM
324
36
0
06 Jul 2023
SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph
  Generation
SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation
Qi Yan
Zhen-Long Liang
Yang Song
Renjie Liao
Lele Wang
DiffM
284
26
0
04 Jul 2023
DiffDTM: A conditional structure-free framework for bioactive molecules
  generation targeted for dual proteins
DiffDTM: A conditional structure-free framework for bioactive molecules generation targeted for dual proteins
Lei Huang
Zheng Yuan
Huihui Yan
Rong Sheng
Linjing Liu
...
Nanjun Chen
Fei Huang
Songfang Huang
Ka-Chun Wong
Yaoyun Zhang
123
1
0
24 Jun 2023
Discrete Graph Auto-Encoder
Discrete Graph Auto-Encoder
Yoann Boget
Magda Gregorova
Alexandros Kalousis
143
6
0
13 Jun 2023
Hyperbolic Graph Diffusion Model
Hyperbolic Graph Diffusion ModelAAAI Conference on Artificial Intelligence (AAAI), 2023
Lingfeng Wen
Xuan Tang
Mingjie Ouyang
Xiangxiang Shen
Jian Yang
Daxin Zhu
Xiao He
Xian Wei
229
9
0
13 Jun 2023
Efficient Approximations of Complete Interatomic Potentials for Crystal
  Property Prediction
Efficient Approximations of Complete Interatomic Potentials for Crystal Property PredictionInternational Conference on Machine Learning (ICML), 2023
Yu-Ching Lin
Keqiang Yan
Youzhi Luo
Lu Dong
Xiaoning Qian
Shuiwang Ji
658
47
0
12 Jun 2023
Molecule Design by Latent Space Energy-Based Modeling and Gradual
  Distribution Shifting
Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution ShiftingConference on Uncertainty in Artificial Intelligence (UAI), 2023
Deqian Kong
Bo Pang
Tian Han
Ying Nian Wu
DiffM
201
6
0
09 Jun 2023
Graph Generation with $K^2$-trees
Graph Generation with K2K^2K2-treesInternational Conference on Learning Representations (ICLR), 2023
Yunhui Jang
Dongwoo Kim
SungSoo Ahn
444
1
0
30 May 2023
MAGNet: Motif-Agnostic Generation of Molecules from Shapes
MAGNet: Motif-Agnostic Generation of Molecules from Shapes
Leon Hetzel
Johanna Sommer
Bastian Rieck
Fabian J. Theis
Stephan Günnemann
350
6
0
30 May 2023
Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation
Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation
Han Huang
Leilei Sun
Bowen Du
Weifeng Lv
DiffM
286
22
0
21 May 2023
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation
MolHF: A Hierarchical Normalizing Flow for Molecular Graph GenerationInternational Joint Conference on Artificial Intelligence (IJCAI), 2023
Yiheng Zhu
Zhenqiu Ouyang
Ben Liao
Jialun Wu
YiXuan Wu
Chang-Yu Hsieh
Tingjun Hou
Jian Wu
AI4CE
261
10
0
15 May 2023
A Latent Diffusion Model for Protein Structure Generation
A Latent Diffusion Model for Protein Structure GenerationLOG IN (LOG IN), 2023
Cong Fu
Keqiang Yan
Limei Wang
Wing Yee Au
Michael McThrow
Tao Komikado
Koji Maruhashi
Kanji Uchino
Xiaoning Qian
Shuiwang Ji
DiffM
248
46
0
06 May 2023
An Equivariant Generative Framework for Molecular Graph-Structure
  Co-Design
An Equivariant Generative Framework for Molecular Graph-Structure Co-DesignbioRxiv (bioRxiv), 2023
Zaixin Zhang
Qi Liu
Cheekong Lee
Chang-Yu Hsieh
Enhong Chen
193
22
0
12 Apr 2023
A Comprehensive Survey on Deep Graph Representation Learning
A Comprehensive Survey on Deep Graph Representation LearningNeural Networks (Neural Netw.), 2023
Wei Ju
Zheng Fang
Yiyang Gu
Zequn Liu
Qingqing Long
...
Jingyang Yuan
Yusheng Zhao
Yifan Wang
Xiao Luo
Ming Zhang
GNNAI4TS
492
255
0
11 Apr 2023
The power of motifs as inductive bias for learning molecular
  distributions
The power of motifs as inductive bias for learning molecular distributions
Johanna Sommer
Leon Hetzel
David Lüdke
Fabian J. Theis
Stephan Günnemann
160
6
0
04 Apr 2023
A Survey on Graph Diffusion Models: Generative AI in Science for
  Molecule, Protein and Material
A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material
Mengchun Zhang
Maryam Qamar
Taegoo Kang
Yuna Jung
Chenshuang Zhang
Sung-Ho Bae
Chaoning Zhang
DiffMMedIm
221
59
0
04 Apr 2023
FairGen: Towards Fair Graph Generation
FairGen: Towards Fair Graph GenerationIEEE International Conference on Data Engineering (ICDE), 2023
Lecheng Zheng
Dawei Zhou
Hanghang Tong
Jiejun Xu
Yada Zhu
Jingrui He
383
14
0
30 Mar 2023
Instance-incremental Scene Graph Generation from Real-world Point Clouds
  via Normalizing Flows
Instance-incremental Scene Graph Generation from Real-world Point Clouds via Normalizing Flows
Chao Qi
Jianqin Yin
Jinghang Xu
Pengxiang Ding
3DPC
223
8
0
21 Feb 2023
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey
  from Precision to Interpretability
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to InterpretabilityACM Computing Surveys (ACM Comput. Surv.), 2023
Zhiqiang Zhong
A. Barkova
Davide Mottin
202
13
0
16 Feb 2023
Graph Generation with Diffusion Mixture
Graph Generation with Diffusion MixtureInternational Conference on Machine Learning (ICML), 2023
Jaehyeong Jo
Dongki Kim
Sung Ju Hwang
DiffM
419
35
0
07 Feb 2023
Generative Diffusion Models on Graphs: Methods and Applications
Generative Diffusion Models on Graphs: Methods and ApplicationsInternational Joint Conference on Artificial Intelligence (IJCAI), 2023
Junfeng Fang
Wenqi Fan
Yunqing Liu
Jiatong Li
Hang Li
Hui Liu
Shucheng Zhou
Qing Li
MedImDiffM
425
84
0
06 Feb 2023
Domain-Agnostic Molecular Generation with Chemical Feedback
Domain-Agnostic Molecular Generation with Chemical FeedbackInternational Conference on Learning Representations (ICLR), 2023
Yin Fang
Ningyu Zhang
Zhuo Chen
Lingbing Guo
Xiaohui Fan
Huajun Chen
351
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0
26 Jan 2023
Conditional Diffusion Based on Discrete Graph Structures for Molecular
  Graph Generation
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph GenerationAAAI Conference on Artificial Intelligence (AAAI), 2023
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Leilei Sun
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GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph
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GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph GenerationIndustrial Conference on Data Mining (IDM), 2022
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Leilei Sun
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Yanjie Fu
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DiffM
209
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04 Dec 2022
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