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2102.00546
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GraphEBM: Molecular Graph Generation with Energy-Based Models
31 January 2021
Meng Liu
Keqiang Yan
Bora Oztekin
Shuiwang Ji
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Papers citing
"GraphEBM: Molecular Graph Generation with Energy-Based Models"
50 / 67 papers shown
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Carola-Bibiane Schönlieb
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07 Aug 2025
Incorporating Inductive Biases to Energy-based Generative Models
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Heterophily-informed Message Passing
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Arno Solin
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28 Apr 2025
Learning Energy-Based Generative Models via Potential Flow: A Variational Principle Approach to Probability Density Homotopy Matching
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Michelle Adeline
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Yu-Hsiang Wang
Vishal Rana
Chetan Rupakheti
Abhishek Pandey
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08 Apr 2025
Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs
Conference on Uncertainty in Artificial Intelligence (UAI), 2025
Milan Papez
Martin Rektoris
Václav Smídl
Tomás Pevný
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412
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15 Mar 2025
InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization
International Conference on Learning Representations (ICLR), 2025
Yifan Niu
Ziqi Gao
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324
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Periodic Materials Generation using Text-Guided Joint Diffusion Model
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Niloy Ganguly
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Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
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Yuhan Chen
Yihong Luo
Yifan Song
Pengwen Dai
Jing Tang
Xiaochun Cao
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25 Feb 2025
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Lorenzo Simone
Marco Podda
Davide Bacciu
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254
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17 Feb 2025
HOG-Diff: Higher-Order Guided Diffusion for Graph Generation
Yiming Huang
Tolga Birdal
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498
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Diffusion Twigs with Loop Guidance for Conditional Graph Generation
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Giangiacomo Mercatali
Yogesh Verma
André Freitas
Vikas Garg
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Jintai Chen
Zhiding Liang
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Samuel Cognolato
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Variational Potential Flow: A Novel Probabilistic Framework for Energy-Based Generative Modelling
Junn Yong Loo
Michelle Adeline
Arghya Pal
Vishnu Monn Baskaran
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Raphaël C.-W. Phan
DiffM
360
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Yaojun Hu
Chenhao Li
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246
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Ryan Rossi
Namyong Park
Huiyuan Chen
Nesreen K. Ahmed
Puja Trivedi
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Danai Koutra
Hanyu Wang
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Variational Flow Matching for Graph Generation
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Floor Eijkelboom
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Jan-Willem van de Meent
529
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Data-Efficient Molecular Generation with Hierarchical Textual Inversion
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Seojin Kim
Jaehyun Nam
Sihyun Yu
Younghoon Shin
Jinwoo Shin
456
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05 May 2024
Complete and Efficient Graph Transformers for Crystal Material Property Prediction
International Conference on Learning Representations (ICLR), 2024
Keqiang Yan
Cong Fu
Xiaofeng Qian
Xiaoning Qian
Shuiwang Ji
425
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18 Mar 2024
CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning
Ulrik Friis-Jensen
Frederik L. Johansen
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Erik B. Dam
Kirsten M. Ø. Jensen
Raghavendra Selvan
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413
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20 Feb 2024
Zero Shot Molecular Generation via Similarity Kernels
Rokas Elijosius
Fabian Zills
Ilyes Batatia
Sam Walton Norwood
D. P. Kovács
Christian Holm
Gábor Csányi
DiffM
265
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Daize Dong
Cheng Tan
Jun Xia
Bozhen Hu
Stan Z. Li
378
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A Simple and Scalable Representation for Graph Generation
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Yunhui Jang
Seul Lee
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309
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Genetic algorithms are strong baselines for molecule generation
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José Miguel Hernández-Lobato
212
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Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel Approach to Generating Molecules with Desirable Properties
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Jihong Guan
Shuigeng Zhou
298
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Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood
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Y. Zhu
Jianwen Xie
Yingnian Wu
Ruiqi Gao
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Xiangyu Zhao
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Yiren Zhao
217
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Autoregressive Diffusion Model for Graph Generation
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Lingkai Kong
Jiaming Cui
Haotian Sun
Yuchen Zhuang
B. Prakash
Chao Zhang
DiffM
252
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Towards Symmetry-Aware Generation of Periodic Materials
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Youzhi Luo
Chengkai Liu
Shuiwang Ji
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422
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Multi-Task Learning with Loop Specific Attention for CDR Structure Prediction
Eleni Giovanoudi
Dimitrios Rafailidis
324
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Hyperbolic Graph Diffusion Model
AAAI Conference on Artificial Intelligence (AAAI), 2023
Lingfeng Wen
Xuan Tang
Mingjie Ouyang
Xiangxiang Shen
Jian Yang
Daxin Zhu
Xiao He
Xian Wei
295
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13 Jun 2023
Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Deqian Kong
Bo Pang
Tian Han
Ying Nian Wu
DiffM
237
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Graph Generation with
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International Conference on Learning Representations (ICLR), 2023
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527
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MAGNet: Motif-Agnostic Generation of Molecules from Shapes
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Johanna Sommer
Bastian Rieck
Fabian J. Theis
Stephan Günnemann
437
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A Latent Diffusion Model for Protein Structure Generation
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Keqiang Yan
Limei Wang
Wing Yee Au
Michael McThrow
Tao Komikado
Koji Maruhashi
Kanji Uchino
Xiaoning Qian
Shuiwang Ji
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356
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DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding
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Meng Liu
X. Li
Lirong Wu
Shuiwang Ji
Tingjun Hou
Stan Z. Li
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Yanwei Lum
Andrew K. Johnston
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361
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