GemNet: Universal Directional Graph Neural Networks for Molecules

2 June 2021

Stephan Günnemann

Papers citing "GemNet: Universal Directional Graph Neural Networks for Molecules"

50 / 237 papers shown

Title
Space Group Equivariant Crystal Diffusion Rees Chang Angela Pak Alex Guerra Ni Zhan Nick Richardson Elif Ertekin Ryan P. Adams 14 0 0 16 May 2025
EDBench: Large-Scale Electron Density Data for Molecular Modeling Hongxin Xiang Ke Li M. Liu Zhixiang Cheng Bin Yao Wenjie Du Jun-Xiong Xia Li Zeng Xin Jin Xiangxiang Zeng 19 0 0 14 May 2025
Towards Faster and More Compact Foundation Models for Molecular Property Prediction Yasir Ghunaim Andrés Villa Gergo Ignacz Gyorgy Szekely Motasem Alfarra Bernard Ghanem AI4CE 90 0 0 28 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
MatterTune: An Integrated, User-Friendly Platform for Fine-Tuning Atomistic Foundation Models to Accelerate Materials Simulation and Discovery Lingyu Kong Nima Shoghi Guoxiang Hu Pan Li Victor Fung 31 0 0 14 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
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
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 60 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 77 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
Improving the Stability of GNN Force Field Models by Reducing Feature Correlation Y. Zeng Wenlong He Ihor Vasyltsov Jiaxin Wei Ying Zhang Lin Chen Yuehua Dai 39 0 0 18 Feb 2025
MatterChat: A Multi-Modal LLM for Material Science Yingheng Tang Wenbin Xu Jie Cao Jianzhu Ma Weilu Gao Steve Farrell Benjamin Erichson Michael W. Mahoney Andy Nonaka 113 3 0 18 Feb 2025
A Periodic Bayesian Flow for Material Generation Hanlin Wu Yuxuan Song Jingjing Gong Ziyao Cao Y. Ouyang Jianbing Zhang Hao Zhou Wei-Ying Ma Jingjing Liu DiffM 69 2 0 04 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
The dark side of the forces: assessing non-conservative force models for atomistic machine learning Filippo Bigi Marcel F. Langer Michele Ceriotti AI4CE 91 7 0 16 Dec 2024
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks Biswadeep Chakraborty H. Kumar Saibal Mukhopadhyay 82 1 0 10 Dec 2024
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective Yushun Dong Patrick Soga Yinhan He Song Wang Jundong Li 94 0 0 10 Dec 2024
OpenQDC: Open Quantum Data Commons Cristian Gabellini Nikhil Shenoy Stephan Thaler Semih Cantürk Daniel McNeela Dominique Beaini Michael Bronstein Prudencio Tossou AI4CE 80 1 0 29 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
Bridging Geometric States via Geometric Diffusion Bridge Shengjie Luo Yixian Xu Di He Shuxin Zheng Tie-Yan Liu Liwei Wang 37 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 30 10 0 31 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 43 2 0 15 Oct 2024
KA-GNN: Kolmogorov-Arnold Graph Neural Networks for Molecular Property Prediction Longlong Li Yipeng Zhang Guanghui Wang Kelin Xia 31 3 0 15 Oct 2024
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning Yuxuan Ren Dihan Zheng Chang-Shu Liu Peiran Jin Yu Shi Lin Huang Jiyan He Shengjie Luo Tao Qin Tie-Yan Liu AI4CE 32 1 0 14 Oct 2024
Towards Stable, Globally Expressive Graph Representations with Laplacian Eigenvectors Junru Zhou Cai Zhou Xiyuan Wang Pan Li Muhan Zhang 37 0 0 13 Oct 2024
Learning Equivariant Non-Local Electron Density Functionals Nicholas Gao Eike Eberhard Stephan Günnemann 28 1 0 10 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
Hydrogen under Pressure as a Benchmark for Machine-Learning Interatomic Potentials Thomas Bischoff Bastian Jäckl Matthias Rupp 24 2 0 20 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 48 0 0 05 Sep 2024
Distribution Learning for Molecular Regression Nima Shoghi Pooya Shoghi Anuroop Sriram Abhishek Das OOD 27 0 0 30 Jul 2024
Enhancing material property prediction with ensemble deep graph convolutional networks Chowdhury Mohammad Abid Rahman Ghadendra B. Bhandari Nasser M. Nasrabadi Aldo H. Romero P. Gyawali AI4CE 48 3 0 26 Jul 2024
FreeCG: Free the Design Space of Clebsch-Gordan Transform for Machine Learning Force Fields Shihao Shao Haoran Geng Zun Wang Qinghua Cui 3DV 40 0 0 02 Jul 2024
On the Expressive Power of Sparse Geometric MPNNs Yonatan Sverdlov Nadav Dym 45 1 0 02 Jul 2024
MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification Tianjun Yao Jiaqi Sun Defu Cao Kun Zhang Guangyi Chen 37 5 0 28 Jun 2024
Improving the Expressiveness of $K$ -hop Message-Passing GNNs by Injecting Contextualized Substructure Information Tianjun Yao Yiongxu Wang Kun Zhang Shangsong Liang 38 11 0 27 Jun 2024
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen Shengjie Luo Di He Shuxin Zheng Tie-Yan Liu Liwei Wang AI4CE 38 5 0 24 Jun 2024
Transferable Boltzmann Generators Leon Klein Frank Noé 46 12 0 20 Jun 2024
A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks Yaochu Jin Xueming Yan Shiqing Liu Xiangyu Wang 49 3 0 19 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin Jacob Helwig Shurui Gui Shuiwang Ji 42 7 0 11 Jun 2024
Grounding Continuous Representations in Geometry: Equivariant Neural Fields David R. Wessels David M. Knigge Samuele Papa Riccardo Valperga Sharvaree P. Vadgama E. Gavves Erik J. Bekkers 47 7 0 09 Jun 2024
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models Zun Wang Chang-Shu Liu Nianlong Zou He Zhang Xinran Wei Lin Huang Lijun Wu Bin Shao 38 1 0 06 Jun 2024
E(n) Equivariant Message Passing Cellular Networks Veljko Kovač Erik J. Bekkers Pietro Lio' Floor Eijkelboom 39 1 0 05 Jun 2024
In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphs Grzegorz Kaszuba Amirhossein D. Naghdi Dario Massa Stefanos Papanikolaou Andrzej Jaszkiewicz Piotr Sankowski AI4CE OODD 40 0 0 03 Jun 2024
Neural Polarization: Toward Electron Density for Molecules by Extending Equivariant Networks Bumju Kwak Jeonghee Jo 53 0 0 01 Jun 2024
Explainable Data-driven Modeling of Adsorption Energy in Heterogeneous Catalysis Tirtha Vinchurkar Janghoon Ock A. Farimani 32 1 0 30 May 2024
A Recipe for Charge Density Prediction Xiang Fu Andrew S. Rosen Kyle Bystrom Rui Wang Albert Musaelian Boris Kozinsky Tess E. Smidt Tommi Jaakkola 50 5 0 29 May 2024
SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning Hongfei Wu Lijun Wu Guoqing Liu Zhirong Liu Bin Shao Zun Wang 43 1 0 26 May 2024
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing Viktor Zaverkin Francesco Alesiani Takashi Maruyama Federico Errica Henrik Christiansen Makoto Takamoto Nicolas Weber Mathias Niepert 46 5 0 23 May 2024
Improved Canonicalization for Model Agnostic Equivariance Siba Smarak Panigrahi Arnab Kumar Mondal 42 3 0 23 May 2024
CaFA: Global Weather Forecasting with Factorized Attention on Sphere Zijie Li Anthony Y. Zhou Saurabh Patil A. Farimani 42 6 0 12 May 2024