GemNet-OC: Developing Graph Neural Networks for Large and Diverse
Molecular Simulation Datasets

GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets

6 April 2022

Johannes Gasteiger

Muhammed Shuaibi

Stephan Günnemann

Zachary W. Ulissi

Papers citing "GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets"

17 / 17 papers shown

Title
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
Pre-training Graph Neural Networks with Structural Fingerprints for Materials Discovery Shuyi Jia Shitij Govil Manav Ramprasad Victor Fung AI4CE 64 1 0 03 Mar 2025
MoMa: A Modular Deep Learning Framework for Material Property Prediction Botian Wang Y. Ouyang Yaohui Li Yixuan Wang Haorui Cui Jianbing Zhang Xiaonan Wang Wei-Ying Ma Hao Zhou 49 0 0 21 Feb 2025
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models Luis Barroso-Luque Muhammed Shuaibi Xiang Fu Brandon M. Wood Misko Dzamba Meng Gao Ammar Rizvi C. L. Zitnick Zachary W. Ulissi AI4CE PINN 41 16 0 16 Oct 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
AdsorbDiff: Adsorbate Placement via Conditional Denoising Diffusion Adeesh Kolluru John R. Kitchin DiffM 47 4 0 07 May 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 36 2 0 07 Feb 2024
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
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions Alvaro Carbonero Alexandre Duval Victor Schmidt Santiago Miret Alex Hernandez-Garcia Yoshua Bengio David Rolnick 32 0 0 10 Oct 2023
FAENet: Frame Averaging Equivariant GNN for Materials Modeling Alexandre Duval Victor Schmidt A. Garcia Santiago Miret Fragkiskos D. Malliaros Yoshua Bengio David Rolnick 34 55 0 28 Apr 2023
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs Saro Passaro C. L. Zitnick 3DPC 34 79 0 07 Feb 2023
AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials Janice Lan Aini Palizhati Muhammed Shuaibi Brandon M. Wood Brook Wander Abhishek Das M. Uyttendaele C. L. Zitnick Zachary W. Ulissi 35 44 0 29 Nov 2022
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations Xiang Fu Zhenghao Wu Wujie Wang T. Xie S. Keten Rafael Gómez-Bombarelli Tommi Jaakkola 32 136 0 13 Oct 2022
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts Richard Tran Janice Lan Muhammed Shuaibi Brandon M. Wood Siddharth Goyal ... Jehad Abed Oleksandr Voznyy Edward H. Sargent Zachary W. Ulissi C. L. Zitnick 28 173 0 17 Jun 2022
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 174 246 0 01 May 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 206 1,240 0 08 Jan 2021
The Open Catalyst 2020 (OC20) Dataset and Community Challenges L. Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi ... Brandon M. Wood Junwoong Yoon Devi Parikh C. L. Zitnick Zachary W. Ulissi 232 503 0 20 Oct 2020