Directional Message Passing for Molecular Graphs

6 March 2020

Stephan Günnemann

Papers citing "Directional Message Passing for Molecular Graphs"

50 / 450 papers shown

Title
HMAE: Self-Supervised Few-Shot Learning for Quantum Spin Systems Ibne Farabi Shihab Sanjeda Akter Anuj Sharma 34 0 0 06 May 2025
RISE: Radius of Influence based Subgraph Extraction for 3D Molecular Graph Explanation J. Qu Wenhan Gao Jiaxing Zhang Xufeng Liu Hua Wei Haibin Ling Y. Liu AI4CE 50 0 0 04 May 2025
A 3D pocket-aware and affinity-guided diffusion model for lead optimization Anjie Qiao Junjie Xie W. R. Huang Hao Zhang Jiahua Rao Shuangjia Zheng Yuedong Yang Z. Wang Guo-Bo Li J. Lei DiffM MedIm 38 0 0 29 Apr 2025
Energy-Based Coarse-Graining in Molecular Dynamics: A Flow-Based Framework Without Data Maximilian Stupp P. S. Koutsourelakis 40 0 0 29 Apr 2025
Uncertainty Quantification in Graph Neural Networks with Shallow Ensembles Tirtha Vinchurkar Kareem Abdelmaqsoud John R. Kitchin AI4CE 91 0 0 17 Apr 2025
Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE J. Firoz Franco Pellegrini Mario Geiger Darren J. Hsu Jenna A. Bilbrey ... Chris Mundy Gábor Csányi Justin S. Smith Ponnuswamy Sadayappan Sutanay Choudhury 26 0 0 14 Apr 2025
Data Fusion of Deep Learned Molecular Embeddings for Property Prediction Robert Appleton Brian C Barnes Alejandro Strachan FedML AI4CE 32 0 0 09 Apr 2025
Quantifying Robustness: A Benchmarking Framework for Deep Learning Forecasting in Cyber-Physical Systems Alexander Windmann Henrik S. Steude Daniel Boschmann Oliver Niggemann OOD AI4TS 33 0 0 04 Apr 2025
Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks Fabian L. Thiemann Thiago Reschützegger Massimiliano Esposito Tseden Taddese Juan D. Olarte-Plata Fausto Martelli AI4CE 47 0 0 31 Mar 2025
Optimal Invariant Bases for Atomistic Machine Learning Alice Allen Emily Shinkle Roxana Bujack Nicholas Lubbers 37 0 0 30 Mar 2025
Multi-Modality Representation Learning for Antibody-Antigen Interactions Prediction Peijin Guo Minghui Li Hewen Pan Ruixiang Huang Lulu Xue Shengqing Hu Zikang Guo Wei Wan Shengshan Hu 29 0 0 22 Mar 2025
Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling Shuqi Lu Xiaohong Ji Bohang Zhang Lin Yao Siyuan Liu Zhifeng Gao Linfeng Zhang Guolin Ke AI4CE 46 1 0 13 Mar 2025
A Generalist Cross-Domain Molecular Learning Framework for Structure-Based Drug Discovery Yiheng Zhu Mingyang Li Junlong Liu Kun Fu J. Wu Q. Li Mingze Yin Jieping Ye Jian Wu Z. Wang 60 0 0 06 Mar 2025
How simple can you go? An off-the-shelf transformer approach to molecular dynamics Max Eissler Tim Korjakow Stefan Ganscha Oliver T. Unke Klaus-Robert Müller Stefan Gugler 58 1 0 03 Mar 2025
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems Yunyang Li Zaishuo Xia Lin Huang Xinran Wei Han Yang ... Zun Wang Chang-Shu Liu Jia Zhang Bin Shao Mark B. Gerstein 72 0 0 26 Feb 2025
A Materials Foundation Model via Hybrid Invariant-Equivariant Architectures Keqiang Yan Montgomery Bohde Andrii Kryvenko Ziyu Xiang Kaiji Zhao ... Jianwen Xie Raymundo Arróyave X. Qian Xiaofeng Qian Shuiwang Ji 47 0 0 25 Feb 2025
Geometric Kolmogorov-Arnold Superposition Theorem Francesco Alesiani Takashi Maruyama H. Christiansen Viktor Zaverkin 53 0 0 23 Feb 2025
MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra Liang Wang Shaozhen Liu Yu Rong Deli Zhao Qiang Liu Shu Wu Liang Wang MedIm 63 2 0 22 Feb 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 97 2 0 21 Feb 2025
SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models Daniel Levy Siba Smarak Panigrahi Sékou-Oumar Kaba Qiang Zhu Kin Long Kelvin Lee Mikhail Galkin Santiago Miret Siamak Ravanbakhsh 189 11 0 05 Feb 2025
Deep Neural Network for Phonon-Assisted Optical Spectra in Semiconductors Qiangqiang Gu S. K. Pandey Zhanghao Zhouyin 59 0 0 02 Feb 2025
FastCHGNet: Training one Universal Interatomic Potential to 1.5 Hours with 32 GPUs Yuanchang Zhou Siyu Hu Chen Wang Lin-Wang Wang Guangming Tan Weile Jia AI4CE GNN 50 0 0 30 Dec 2024
MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights Jingjing Hu D. Guo Zhan Si Deguang Liu Yunfeng Diao J. Zhang Jinxing Zhou Meng Wang Mamba 98 1 0 21 Dec 2024
LMDM:Latent Molecular Diffusion Model For 3D Molecule Generation Xiang Chen DiffM 74 0 0 05 Dec 2024
OpenQDC: Open Quantum Data Commons Cristian Gabellini Nikhil Shenoy Stephan Thaler Semih Cantürk Daniel McNeela Dominique Beaini Michael Bronstein Prudencio Tossou AI4CE 75 1 0 29 Nov 2024
Geometric Point Attention Transformer for 3D Shape Reassembly Jiahan Li Chaoran Cheng Jianzhu Ma Ge Liu 3DPC ViT 74 1 0 26 Nov 2024
Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction Zhao Xu Haiyang Yu Montgomery Bohde Shuiwang Ji 40 0 0 06 Nov 2024
Integrating Graph Neural Networks and Many-Body Expansion Theory for Potential Energy Surfaces Siqi Chen Zhiqiang Wang Xianqi Deng Yili Shen C. Ju ... Lin Xiong Guo Ling Dieaa Alhmoud Hui Guan Zhou Lin 29 0 0 03 Nov 2024
Bridging Geometric States via Geometric Diffusion Bridge Shengjie Luo Yixian Xu Di He Shuxin Zheng Tie-Yan Liu Liwei Wang 34 0 0 31 Oct 2024
The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains Eric Qu Aditi S. Krishnapriyan LRM 26 10 0 31 Oct 2024
Scaling Molecular Dynamics with ab initio Accuracy to 149 Nanoseconds per Day Jianxiong Li Boyang Li Zhuoqiang Guo Mingzhen Li Enji Li Lijun Liu Guojun Yuan Zhan Wang Guangming Tan Weile Jia AI4CE 35 1 0 30 Oct 2024
ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation Majdi Hassan Nikhil Shenoy Jungyoon Lee Hannes Stärk Stephan Thaler Dominique Beaini 27 6 0 29 Oct 2024
Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling and Zero-Shot Transfer Zihan Pengmei Zhengyuan Shen Zichen Wang Marcus Collins Huzefa Rangwala AI4CE 21 2 0 29 Oct 2024
Relaxed Equivariance via Multitask Learning Ahmed A. A. Elhag T. Konstantin Rusch Francesco Di Giovanni Michael Bronstein 42 2 0 23 Oct 2024
Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance Dominik Fuchsgruber Tim Poštuvan Stephan Günnemann Simon Geisler 34 2 0 22 Oct 2024
CrystalX: Ultra-Precision Crystal Structure Resolution and Error Correction Using Deep Learning Kaipeng Zheng Weiran Huang Wanli Ouyang Han-Sen Zhong Y. Li 31 0 0 17 Oct 2024
Partially Trained Graph Convolutional Networks Resist Oversmoothing Dimitrios Kelesis Dimitris Fotakis G. Paliouras SSL 16 0 0 17 Oct 2024
Geometric Trajectory Diffusion Models Jiaqi Han Minkai Xu Aaron Lou Haotian Ye Stefano Ermon DiffM 51 4 0 16 Oct 2024
Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks? Jiacheng Cen Anyi Li Ning Lin Yuxiang Ren Zihe Wang Wenbing Huang 38 2 0 15 Oct 2024
KA-GNN: Kolmogorov-Arnold Graph Neural Networks for Molecular Property Prediction Longlong Li Yipeng Zhang Guanghui Wang Kelin Xia 29 3 0 15 Oct 2024
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction Junjie Xu Artem Moskalev Tommaso Mansi Mangal Prakash Rui Liao AI4CE 26 1 0 15 Oct 2024
Towards Stable, Globally Expressive Graph Representations with Laplacian Eigenvectors Junru Zhou Cai Zhou Xiyuan Wang Pan Li Muhan Zhang 35 0 0 13 Oct 2024
E3STO: Orbital Inspired SE(3)-Equivariant Molecular Representation for Electron Density Prediction Ilan Mitnikov Joseph Jacobson 20 0 0 08 Oct 2024
Neural P $^3$ M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs Yusong Wang Chaoran Cheng Shaoning Li Yuxuan Ren Bin Shao Ge Liu Pheng-Ann Heng Nanning Zheng AI4CE 30 3 0 26 Sep 2024
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks Ashwin Samudre Mircea Petrache Brian D. Nord Shubhendu Trivedi 42 2 0 18 Sep 2024
SpinMultiNet: Neural Network Potential Incorporating Spin Degrees of Freedom with Multi-Task Learning Koki Ueno Satoru Ohuchi Kazuhide Ichikawa Kei Amii Kensuke Wakasugi 46 0 0 05 Sep 2024
Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features Thomas Schnake Farnoush Rezaei Jafaria Jonas Lederer Ping Xiong Shinichi Nakajima Stefan Gugler G. Montavon Klaus-Robert Müller 38 3 0 30 Aug 2024
chemtrain: Learning Deep Potential Models via Automatic Differentiation and Statistical Physics Paul Fuchs Stephan Thaler Sebastien Röcken J. Zavadlav DiffM 68 6 0 28 Aug 2024
Cross-Modal Learning for Chemistry Property Prediction: Large Language Models Meet Graph Machine Learning Sakhinana Sagar Srinivas Venkataramana Runkana AI4CE 33 1 0 27 Aug 2024
Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small Models Tianyu Zhang Yuxiang Ren Chengbin Hou Hairong Lv Xuegong Zhang AI4CE 29 1 0 19 Aug 2024