Top-N: Equivariant set and graph generation without exchangeability

5 October 2021

Papers citing "Top-N: Equivariant set and graph generation without exchangeability"

28 / 28 papers shown

Title
Improving Equivariant Networks with Probabilistic Symmetry Breaking Hannah Lawrence Vasco Portilheiro Yan Zhang Sékou-Oumar Kaba 32 3 0 27 Mar 2025
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks Maya Bechler-Speicher Ben Finkelshtein Fabrizio Frasca Luis Muller Jan Tonshoff ... Michael M. Bronstein Mathias Niepert Bryan Perozzi Mikhail Galkin Christopher Morris OOD 92 2 0 21 Feb 2025
Score-based 3D molecule generation with neural fields Matthieu Kirchmeyer Pedro H. O. Pinheiro Saeed Saremi DiffM 35 0 0 15 Jan 2025
Geometric Representation Condition Improves Equivariant Molecule Generation Zian Li Cai Zhou Xiyuan Wang Xingang Peng Muhan Zhang 27 1 0 04 Oct 2024
Generative Modelling of Structurally Constrained Graphs Manuel Madeira Clément Vignac D. Thanou Pascal Frossard DiffM 29 0 0 25 Jun 2024
Discrete-state Continuous-time Diffusion for Graph Generation Zhe Xu Ruizhong Qiu Yuzhong Chen Huiyuan Chen Xiran Fan Menghai Pan Zhichen Zeng Mahashweta Das Hanghang Tong 14 0 0 19 May 2024
A Review on Fragment-based De Novo 2D Molecule Generation Sergei Voloboev VLM 19 0 0 08 May 2024
A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation Xiangru Tang Howard Dai Elizabeth Knight Fang Wu Yunyang Li Tianxiao Li Mark B. Gerstein 12 24 0 13 Feb 2024
Interpreting Equivariant Representations Andreas Abildtrup Hansen Anna Calissano Aasa Feragen 27 1 0 23 Jan 2024
Symmetry Breaking and Equivariant Neural Networks Sekouba Kaba Siamak Ravanbakhsh 19 11 0 14 Dec 2023
SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation Qi Yan Zhen-Long Liang Yang Song Renjie Liao Lele Wang DiffM 33 18 0 04 Jul 2023
Hyperbolic Graph Diffusion Model Lingfeng Wen Xuan Tang Mingjie Ouyang Xiangxiang Shen Jian Yang Daxin Zhu Mingsong Chen Xian Wei 21 1 0 13 Jun 2023
Trans-Dimensional Generative Modeling via Jump Diffusion Models Andrew Campbell William Harvey Christian Weilbach Valentin De Bortoli Tom Rainforth Arnaud Doucet DiffM 21 2 0 25 May 2023
Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D Bo Qiang Yuxuan Song Minkai Xu Jingjing Gong B. Gao Hao Zhou Weiying Ma Yanyan Lan DiffM 30 5 0 05 May 2023
MUDiff: Unified Diffusion for Complete Molecule Generation Chenqing Hua Sitao Luan Minkai Xu Rex Ying Jie Fu Stefano Ermon Doina Precup DiffM 25 34 0 28 Apr 2023
Bridging the Gap between Chemical Reaction Pretraining and Conditional Molecule Generation with a Unified Model Bo Qiang Yiran Zhou Yuheng Ding Ningfeng Liu Song Song L. Zhang Bowei Huang Zhenming Liu AI4CE 10 4 0 13 Mar 2023
MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation Clément Vignac Nagham Osman Laura Toni P. Frossard DiffM 22 33 0 17 Feb 2023
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation Han Huang Leilei Sun Bowen Du Weifeng Lv 17 24 0 01 Jan 2023
Diffusion Models for Graphs Benefit From Discrete State Spaces K. Haefeli Karolis Martinkus Nathanael Perraudin Roger Wattenhofer DiffM 66 36 0 04 Oct 2022
Graph Neural Networks for Molecules Yuyang Wang Zijie Li A. Farimani GNN AI4CE 33 20 0 12 Sep 2022
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators Karolis Martinkus Andreas Loukas Nathanael Perraudin Roger Wattenhofer 10 49 0 04 Apr 2022
Equivariant Diffusion for Molecule Generation in 3D Emiel Hoogeboom Victor Garcia Satorras Clément Vignac Max Welling DiffM 15 409 0 31 Mar 2022
A Survey on Deep Graph Generation: Methods and Applications Yanqiao Zhu Yuanqi Du Yinkai Wang Yichen Xu Jieyu Zhang Qiang Liu Shu Wu 3DV GNN 16 40 0 13 Mar 2022
ReGAE: Graph autoencoder based on recursive neural networks Adam Malkowski Jakub Grzechociñski Pawel Wawrzyñski GNN 6 0 0 28 Jan 2022
Generating stable molecules using imitation and reinforcement learning S. A. Meldgaard Jonas Köhler H. L. Mortensen Mads-Peter V. Christiansen Frank Noé B. Hammer 133 12 0 11 Jul 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 161 948 0 27 Apr 2021
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 143 289 0 05 Nov 2018
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 152 1,748 0 02 Mar 2017