FAENet: Frame Averaging Equivariant GNN for Materials Modeling

28 April 2023

Fragkiskos D. Malliaros

Yoshua Bengio

David Rolnick

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Papers citing "FAENet: Frame Averaging Equivariant GNN for Materials Modeling"

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Title
COSMOS: Continuous Simplicial Neural Networks Aref Einizade Dorina Thanou Fragkiskos D. Malliaros Jhony H. Giraldo AI4CE 53 0 0 17 Mar 2025
ELECTRA: A Symmetry-breaking Cartesian Network for Charge Density Prediction with Floating Orbitals Jonas Elsborg Luca Thiede Alán Aspuru-Guzik T. Vegge Arghya Bhowmik 31 0 0 11 Mar 2025
CrystalFramer: Rethinking the Role of Frames for SE(3)-Invariant Crystal Structure Modeling Yusei Ito Tatsunori Taniai Ryo Igarashi Yoshitaka Ushiku K. Ono 57 0 0 04 Mar 2025
Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schr\"odinger Equation Kevin Han Huang Ni Zhan Elif Ertekin Peter Orbanz Ryan P. Adams 50 0 0 07 Feb 2025
Higher-Order GNNs Meet Efficiency: Sparse Sobolev Graph Neural Networks Jhony H. Giraldo Aref Einizade Andjela Todorovic Jhon A. Castro-Correa Mohsen Badiey T. Bouwmans Fragkiskos D. Malliaros 26 0 0 07 Nov 2024
Relaxed Equivariance via Multitask Learning Ahmed A. A. Elhag T. Konstantin Rusch Francesco Di Giovanni Michael Bronstein 42 2 0 23 Oct 2024
Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases Cristian Meo Akihiro Nakano Mircea Lica Aniket Didolkar Masahiro Suzuki Anirudh Goyal Mengmi Zhang Justin Dauwels Y. Matsuo Yoshua Bengio OCL 28 0 0 21 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
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
On the design space between molecular mechanics and machine learning force fields Yuanqing Wang Kenichiro Takaba Michael S. Chen Marcus Wieder Yuzhi Xu ... Kyunghyun Cho Joe G. Greener Peter K. Eastman Stefano Martiniani M. Tuckerman AI4CE 29 4 0 03 Sep 2024
Improving Molecular Modeling with Geometric GNNs: an Empirical Study Ali Ramlaoui Théo Saulus Basile Terver Victor Schmidt David Rolnick Fragkiskos D. Malliaros Alexandre Duval AI4CE 20 1 0 11 Jul 2024
Probing the effects of broken symmetries in machine learning Marcel F. Langer Sergey Pozdnyakov Michele Ceriotti AI4CE 26 0 0 25 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin Jacob Helwig Shurui Gui Shuiwang Ji 26 7 0 11 Jun 2024
E $^3$ -Net: Efficient E(3)-Equivariant Normal Estimation Network Hanxiao Wang Mingyang Zhao Weize Quan Zhen Chen Dong-ming Yan Peter Wonka 3DPC 31 0 0 01 Jun 2024
Predicting solvation free energies with an implicit solvent machine learning potential Sebastien Röcken A. F. Burnet J. Zavadlav AI4Cl AI4CE 42 3 0 31 May 2024
Improved Canonicalization for Model Agnostic Equivariance Siba Smarak Panigrahi Arnab Kumar Mondal 18 3 0 23 May 2024
Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction Jhon A. Castro-Correa Jhony H. Giraldo Mohsen Badiey Fragkiskos D. Malliaros 20 5 0 28 Mar 2024
Application-Driven Innovation in Machine Learning David Rolnick Alán Aspuru-Guzik Sara Beery B. Dilkina P. Donti ... Hannah Kerner C. Monteleoni Esther Rolf Milind Tambe Adam White 25 2 0 26 Mar 2024
Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding Tatsunori Taniai Ryo Igarashi Yuta Suzuki Naoya Chiba Kotaro Saito Yoshitaka Ushiku K. Ono 28 8 0 18 Mar 2024
Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields Yi-Lun Liao Tess E. Smidt Abhishek Das DiffM AI4CE 19 10 0 14 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 29 20 0 01 Mar 2024
Equivariant Frames and the Impossibility of Continuous Canonicalization Nadav Dym Hannah Lawrence Jonathan W. Siegel 23 16 0 25 Feb 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 23 2 0 07 Feb 2024
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks Haoyu Li Shichang Zhang Longwen Tang Mathieu Bauchy Yizhou Sun AI4CE 29 0 0 08 Dec 2023
Reflection-Equivariant Diffusion for 3D Structure Determination from Isotopologue Rotational Spectra in Natural Abundance Austin H. Cheng Alston Lo Santiago Miret Brooks H Pate Alán Aspuru-Guzik 18 4 0 17 Oct 2023
Efficient Model-Agnostic Multi-Group Equivariant Networks Razan Baltaji Sourya Basu L. Varshney 13 1 0 14 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 19 0 0 10 Oct 2023
MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling Kin Long Kelvin Lee Carmelo Gonzales Marcel Nassar Matthew Spellings Mikhail Galkin Santiago Miret 16 15 0 12 Sep 2023
Smooth, exact rotational symmetrization for deep learning on point clouds Sergey Pozdnyakov Michele Ceriotti 3DPC 24 25 0 30 May 2023
Efficient Equivariant Transfer Learning from Pretrained Models Sourya Basu Pulkit Katdare P. Sattigeri Vijil Chenthamarakshan Katherine Driggs Campbell Payel Das L. Varshney 19 7 0 17 May 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks Weitao Du Yuanqi Du Limei Wang Dieqiao Feng Guifeng Wang Shuiwang Ji Carla P. Gomes Zhixin Ma AI4CE 13 33 0 07 Apr 2023
On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks Jhony H. Giraldo Konstantinos Skianis T. Bouwmans Fragkiskos D. Malliaros 13 45 0 05 Dec 2022
Frame Averaging for Invariant and Equivariant Network Design Omri Puny Matan Atzmon Heli Ben-Hamu Ishan Misra Aditya Grover Edward James Smith Y. Lipman FedML 33 90 0 07 Oct 2021
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 142 242 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 183 1,218 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 207 370 0 20 Oct 2020