Equivariant Networks for Crystal Structures

15 November 2022

Papers citing "Equivariant Networks for Crystal Structures"

23 / 23 papers shown

Title
Improving Equivariant Networks with Probabilistic Symmetry Breaking Hannah Lawrence Vasco Portilheiro Yan Zhang Sékou-Oumar Kaba 40 3 0 27 Mar 2025
Symmetry-Informed Graph Neural Networks for Carbon Dioxide Isotherm and Adsorption Prediction in Aluminum-Substituted Zeolites M. Petković José-Manuel Vicent Luna El\=ıza Beate Dinne Vlado Menkovski Sofía Calero AI4CE 35 0 0 26 Mar 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 99 11 0 05 Feb 2025
Supra-Laplacian Encoding for Transformer on Dynamic Graphs Yannis Karmim Marc Lafon Raphael Fournier SÑiehotta Nicolas Thome 20 0 0 26 Sep 2024
Improved Canonicalization for Model Agnostic Equivariance Siba Smarak Panigrahi Arnab Kumar Mondal 18 3 0 23 May 2024
Graph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged Zeolites Marko Petković J. M. Vicent‐Luna Vlado Menkovski Sofía Calero 16 0 0 19 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 32 20 0 01 Mar 2024
Symmetry Breaking and Equivariant Neural Networks Sekouba Kaba Siamak Ravanbakhsh 27 11 0 14 Dec 2023
LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions Andre Niyongabo Rubungo Craig Arnold Barry P. Rand Adji Bousso Dieng AI4CE 12 25 0 21 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 19 15 0 12 Sep 2023
M $^2$ Hub: Unlocking the Potential of Machine Learning for Materials Discovery Yuanqi Du Yingheng Wang Yin-Hua Huang Jianan Canal Li Yanqiao Zhu T. Xie Chenru Duan J. Gregoire Carla P. Gomes 19 6 0 14 Jun 2023
Equivariant Parameter Sharing for Porous Crystalline Materials Marko Petković Pablo Romero-Marimon Vlado Menkovski Sofía Calero 6 1 0 04 Apr 2023
Densely Connected $G$ -invariant Deep Neural Networks with Signed Permutation Representations Devanshu Agrawal James Ostrowski AI4CE 8 0 0 08 Mar 2023
Implicit Convolutional Kernels for Steerable CNNs Maksim Zhdanov Nico Hoffmann Gabriele Cesa 13 5 0 12 Dec 2022
Domain-informed graph neural networks: a quantum chemistry case study Jay Morgan A. Paiement C. Klinke GNN 19 4 0 25 Aug 2022
Crystal Diffusion Variational Autoencoder for Periodic Material Generation Tian Xie Xiang Fu O. Ganea Regina Barzilay Tommi Jaakkola DiffM BDL 196 224 0 12 Oct 2021
Automatic Symmetry Discovery with Lie Algebra Convolutional Network Nima Dehmamy Robin G. Walters Yanchen Liu Dashun Wang Rose Yu AI4CE 73 80 0 15 Sep 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 163 1,095 0 27 Apr 2021
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 71 185 0 19 Apr 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
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 146 289 0 05 Nov 2018
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 210 13,886 0 02 Dec 2016