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
AdsorbDiff: Adsorbate Placement via Conditional Denoising Diffusion Adeesh Kolluru John R. Kitchin DiffM 47 4 0 07 May 2024
Graph as Point Set Xiyuan Wang Pan Li Muhan Zhang GNN 3DPC PINN 44 4 0 05 May 2024
Lightweight Geometric Deep Learning for Molecular Modelling in Catalyst Discovery Patrick Geitner GNN 31 0 0 05 Apr 2024
GeoT: Tensor Centric Library for Graph Neural Network via Efficient Segment Reduction on GPU Zhongming Yu Genghan Zhang Hanxian Huang Xin Chen Jishen Zhao GNN 29 0 0 03 Apr 2024
RiEMann: Near Real-Time SE(3)-Equivariant Robot Manipulation without Point Cloud Segmentation Chongkai Gao Zhengrong Xue Shuying Deng Tianhai Liang Siqi Yang Lin Shao Huazhe Xu 3DPC 39 10 0 28 Mar 2024
AKBR: Learning Adaptive Kernel-based Representations for Graph Classification Feifei Qian Lixin Cui Yue Wang Hangyuan Du Lu Bai Edwin R. Hancock 21 0 0 24 Mar 2024
Complete and Efficient Graph Transformers for Crystal Material Property Prediction Keqiang Yan Cong Fu Xiaofeng Qian Xiaoning Qian Shuiwang Ji 46 19 0 18 Mar 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications Jiaqi Han Jiacheng Cen Liming Wu Zongzhao Li Xiangzhe Kong ... Zhewei Wei Deli Zhao Yu Rong Wenbing Huang Wenbing Huang AI4CE 34 20 0 01 Mar 2024
Pretraining Strategy for Neural Potentials Zehua Zhang Zijie Li A. Farimani AI4CE 44 0 0 24 Feb 2024
ChemReasoner: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback Henry W Sprueill Carl N. Edwards Khushbu Agarwal Mariefel V. Olarte Udishnu Sanyal Conrad Johnston Hongbin Liu Heng Ji Sutanay Choudhury LRM 33 7 0 15 Feb 2024
Cartesian atomic cluster expansion for machine learning interatomic potentials Bingqing Cheng 39 31 0 12 Feb 2024
Impact of Domain Knowledge and Multi-Modality on Intelligent Molecular Property Prediction: A Systematic Survey Taojie Kuang Pengfei Liu Zhixiang Ren AI4CE 47 1 0 11 Feb 2024
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics Artur P. Toshev Jonas A. Erbesdobler Nikolaus A. Adams Johannes Brandstetter AI4CE 46 4 0 09 Feb 2024
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers Md Shamim Hussain Mohammed J. Zaki D. Subramanian ViT 33 5 0 07 Feb 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 36 2 0 07 Feb 2024
Weisfeiler Leman for Euclidean Equivariant Machine Learning Snir Hordan Tal Amir Nadav Dym 44 5 0 04 Feb 2024
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks D. M. Nguyen Nina Lukashina Tai Nguyen An T. Le TrungTin Nguyen Nhat Ho Jan Peters Daniel Sonntag Viktor Zaverkin Mathias Niepert 33 5 0 03 Feb 2024
Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction Kangkang Lu Yanhua Yu Hao Fei Xuan Li Zixuan Yang Zirui Guo Meiyu Liang Mengran Yin Tat-Seng Chua 26 3 0 28 Jan 2024
Bimanual Deformable Bag Manipulation Using a Structure-of-Interest Based Latent Dynamics Model Peng Zhou Pai Zheng Jiaming Qi Chenxi Li Chenguang Yang D. Navarro-Alarcon Jia Pan AI4CE 22 1 0 21 Jan 2024
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products Shengjie Luo Tianlang Chen Aditi S. Krishnapriyan 30 19 0 18 Jan 2024
A Characterization Theorem for Equivariant Networks with Point-wise Activations Marco Pacini Xiaowen Dong Bruno Lepri G. Santin 44 2 0 17 Jan 2024
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study Sadman Sadeed Omee Nihang Fu Rongzhi Dong Ming Hu Jianjun Hu OOD 31 17 0 16 Jan 2024
Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry Zeyu Wang Tianyi Jiang Jinhuan Wang Qi Xuan AI4CE 27 8 0 07 Jan 2024
Graph Elimination Networks Shuo Wang Ge Cheng Yun Zhang AI4CE GNN 26 0 0 02 Jan 2024
Accelerating the prediction of inorganic surfaces with machine learning interatomic potentials Kyle Noordhoek Christopher J. Bartel AI4CE 22 6 0 18 Dec 2023
SE(3)-Invariant Multiparameter Persistent Homology for Chiral-Sensitive Molecular Property Prediction Andac Demir Francis Prael B. Kiziltan 19 2 0 12 Dec 2023
Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials Viktor Zaverkin David Holzmüller Henrik Christiansen Federico Errica Francesco Alesiani Makoto Takamoto Mathias Niepert Johannes Kastner AI4CE 29 13 0 03 Dec 2023
PerCNet: Periodic Complete Representation for Crystal Graphs Jiao Huang Qianli Xing Jinglong Ji Bo Yang 34 1 0 03 Dec 2023
Multiparameter Persistent Homology for Molecular Property Prediction Andac Demir B. Kiziltan 22 1 0 17 Nov 2023
STRIDE: Structure-guided Generation for Inverse Design of Molecules Shehtab Zaman D. Akhiyarov Mauricio Araya-Polo Kenneth Chiu 23 1 0 06 Nov 2023
Gradual Optimization Learning for Conformational Energy Minimization Artem Tsypin L. Ugadiarov Kuzma Khrabrov Alexander Telepov Egor Rumiantsev Alexey Skrynnik Aleksandr I. Panov Dmitry Vetrov E. Tutubalina Artur Kadurin 24 1 0 05 Nov 2023
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method Yuyan Ni Shikun Feng Wei-Ying Ma Zhiming Ma Yanyan Lan DiffM AI4CE 32 10 0 03 Nov 2023
Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs Yeyuan Chen Dingmin Wang 19 0 0 03 Nov 2023
Investigating the Behavior of Diffusion Models for Accelerating Electronic Structure Calculations D. Rothchild Andrew S. Rosen Eric Taw Connie Robinson Joseph E. Gonzalez Aditi S. Krishnapriyan DiffM 26 2 0 02 Nov 2023
The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture Anuroop Sriram Sihoon Choi Xiaohan Yu Logan M. Brabson Abhishek Das Zachary W. Ulissi Matthew Uyttendaele A. Medford D. Sholl AI4CE 27 35 0 01 Nov 2023
Role of Structural and Conformational Diversity for Machine Learning Potentials Nikhil Shenoy Prudencio Tossou Emmanuel Noutahi Hadrien Mary Dominique Beaini Jiarui Ding AI4CE 19 0 0 30 Oct 2023
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach Phillip Pope David Jacobs 24 3 0 28 Oct 2023
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction Nima Shoghi Adeesh Kolluru John R. Kitchin Zachary W. Ulissi C. L. Zitnick Brandon M. Wood AI4CE 24 32 0 25 Oct 2023
Monte Carlo Thought Search: Large Language Model Querying for Complex Scientific Reasoning in Catalyst Design Henry W Sprueill Carl N. Edwards Mariefel V. Olarte Udishnu Sanyal Heng Ji Sutanay Choudhury LRM 34 10 0 22 Oct 2023
Learning Interatomic Potentials at Multiple Scales Xiang Fu Albert Musaelian Anders Johansson Tommi Jaakkola Boris Kozinsky 29 2 0 20 Oct 2023
MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design Xiang Fu Tian Xie Andrew S. Rosen Tommi Jaakkola Jake A. Smith DiffM 42 9 0 16 Oct 2023
Latent Conservative Objective Models for Data-Driven Crystal Structure Prediction Han Qi Xinyang Geng Stefano Rando Iku Ohama Aviral Kumar Sergey Levine DiffM 42 2 0 16 Oct 2023
Data-Driven Score-Based Models for Generating Stable Structures with Adaptive Crystal Cells Arsen Sultanov J. Crivello Tabea Rebafka Nataliya Sokolovska DiffM 29 6 0 16 Oct 2023
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets Dominique Beaini Shenyang Huang Joao Alex Cunha Zhiyi Li Gabriela Moisescu-Pareja ... Thérence Bois Andrew Fitzgibbon Bla.zej Banaszewski Chad Martin Dominic Masters AI4CE 28 19 0 06 Oct 2023
Fast, Expressive SE $(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space Erik J. Bekkers Sharvaree P. Vadgama Rob D. Hesselink P. A. V. D. Linden David W. Romero 15 24 0 04 Oct 2023
Spline-based neural network interatomic potentials: blending classical and machine learning models Joshua A Vita D. Trinkle 14 2 0 04 Oct 2023
On Training Derivative-Constrained Neural Networks KaiChieh Lo Daniel Huang 26 3 0 02 Oct 2023
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks Yanqiao Zhu Jeehyun Hwang Keir Adams Zhen Liu B. Nan ... Olaf Wiest Olexandr Isayev Connor W. Coley Yizhou Sun Wei Wang 24 6 0 29 Sep 2023
From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields J. Frank Oliver T. Unke Klaus-Robert Muller Stefan Chmiela 26 3 0 21 Sep 2023
Uncovering Neural Scaling Laws in Molecular Representation Learning Dingshuo Chen Yanqiao Zhu Jieyu Zhang Yuanqi Du Zhixun Li Qiang Liu Shu Wu Liang Wang 32 16 0 15 Sep 2023