Articles Citing

Finding symmetry breaking order parameters with Euclidean neural networks

Tess E. Smidt ^1,2,*, Mario Geiger^1,3, and Benjamin Kurt Miller ^1,2,4

¹Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
²Center for Advanced Mathematics for Energy Research Applications (CAMERA), Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
³Department of Physics, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
⁴Department of Mathematics, Freie Universität Berlin, Berlin 14195, Germany

^*tsmidt@lbl.gov

Representation learning of crystal materials using Graph Neural Networks: Passive symmetry challenges and advances

Jie Cui, Chenglei Han, Jiyao Liang, Lin Li, and Fei Wang

Science Progress 109 00368504261446462 (2026)

Graph-theoretic active learning for the closed-loop discovery of stochastic heterogeneous composites

Lei Qiu, Shuxin Zhang, Yongbin Yang, Mengdie Wang, and Mohammad Reza Maghami

PLoS One 21 e0353692 (2026)

A geometric rotation-equivariant spherical convolutional and gaussian radial basis network for predicting protein-ligand binding affinity

Bin Wan, Gaili Li, and Ruisheng Zhang

Multimedia Systems 32 489 (2026)

Algebraic Stabilization of Linear Transformations in Artificial Neural Networks

Kostadin Yotov, Emil Hadzhikolev, and Stanka Hadzhikoleva

Mathematics 14 623 (2026)

Relevance of 3D Rotationally Equivariant Neural Networks for Predicting Protein-Ligand Binding Affinities

Gaili Li, Yongna Yuan, and Ruisheng Zhang

Interdiscip Sci Comput Life Sci 18 392 (2026)

Future-oriented precision creation: recent advances in the intelligent design and synthesis of fine chemicals

Junpeng Chen, Qilei Liu, and Lei Zhang

ENG. Chem. Eng. 20 35 (2026)

Physical Constraint Frameworks in Chemistry: From Traditional Descriptors to Equivariant Neural Networks

Zhenxing Zhu, Sirui Zhao, Diandong Tang, Jingyu Guo, and Lin Shen

Communications in Computational Chemistry 8 249 (2026)

No title available

Bing Han, Ruitao Pan, Yumin Chen, Peixin Hong, Weiyuan Liu, Chenxi Wang, Zhibin Zhao, and Zhi Zhai

An Intrusion Detection Method Based on Symmetric Federated Deep Learning in Complex Networks

Lei Wang, Xuanrui Ren, and Chunyi Wu

Symmetry 17 952 (2025)

Functions on Symmetric Matrices and Point Clouds via Lightweight Invariant Features from Galois Theory

Ben Blum-Smith, Ningyuan (Teresa) Huang, Marco Cuturi, and Soledad Villar

SIAM J. Appl. Algebra Geometry 9 902 (2025)

Dielectric tensor of perovskite oxides at finite temperature using equivariant graph neural network potentials

Alex Kutana, Koki Yoshimochi, and Ryoji Asahi

Science and Technology of Advanced Materials: Methods 5 2497254 (2025)

Learning PDFs through interpretable latent representations in Mellin space

Brandon Kriesten and T. J. Hobbs

Phys. Rev. D 111 014028 (2025)

Acceleration of crystal structure relaxation with deep reinforcement learning

Elena Trukhan, Efim Mazhnik, and Artem R. Oganov

npj Comput Mater 11 290 (2025)

SuperMetal: a generative AI framework for rapid and precise metal ion location prediction in proteins

Xiaobo Lin, Zhaoqian Su, Yunchao Lance Liu, Jingxian Liu, Xiaohan Kuang, Peter T. Cummings, Jesse Spencer-Smith, and Jens Meiler

J Cheminform 17 107 (2025)

Artificial intelligence for science in quantum, atomistic, and continuum systems

Xuan Zhang et al.

Foundations and Trends® in Machine Learning 18 385 (2025)

Discovery of highly anisotropic dielectric crystals with equivariant graph neural networks

Yuchen Lou and Alex M. Ganose

Faraday Discuss. 256 255 (2025)

Equivariant neural network force fields for magnetic materials

Zilong Yuan, Zhiming Xu, He Li, Xinle Cheng, Honggeng Tao, Zechen Tang, Zhiyuan Zhou, Wenhui Duan, and Yong Xu

Quantum Front 3 8 (2024)

Quantifying chemical short-range order in metallic alloys

Killian Sheriff, Yifan Cao, Tess Smidt, and Rodrigo Freitas

Proc. Natl. Acad. Sci. U.S.A. 121 e2322962121 (2024)

Building an ab initio solvated DNA model using Euclidean neural networks

Alex J. Lee, Joshua A. Rackers, Shivesh Pathak, William P. Bricker, and Kshatresh Dutta Dubey

PLoS ONE 19 e0297502 (2024)

Predicting magnetic properties of van der Waals magnets using graph neural networks

Peter Minch, Romakanta Bhattarai, Kamal Choudhary, and Trevor David Rhone

Phys. Rev. Materials 8 114002 (2024)

Chemical-motif characterization of short-range order with E(3)-equivariant graph neural networks

Killian Sheriff, Yifan Cao, and Rodrigo Freitas

npj Comput Mater 10 215 (2024)

A snapshot review on soft materials assembly design utilizing machine learning methods

Maya M. Martirossyan, Hongjin Du, Julia Dshemuchadse, and Chrisy Xiyu Du

MRS Advances 9 1088 (2024)

Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview

Andre Nicolle, Sili Deng, Matthias Ihme, Nursulu Kuzhagaliyeva, Emad Al Ibrahim, and Aamir Farooq

J. Chem. Inf. Model. 64 597 (2024)

Recent developments at the intersection of AI and theoretical physics

Fabian Ruehle

Contemporary Physics 65 180 (2024)

PharmRL: pharmacophore elucidation with deep geometric reinforcement learning

Rishal Aggarwal and David R. Koes

BMC Biol 22 301 (2024)

Select page:

Physical Review Research

Filter

Articles Citing

Finding symmetry breaking order parameters with Euclidean neural networks

Representation learning of crystal materials using Graph Neural Networks: Passive symmetry challenges and advances

Graph-theoretic active learning for the closed-loop discovery of stochastic heterogeneous composites

A geometric rotation-equivariant spherical convolutional and gaussian radial basis network for predicting protein-ligand binding affinity

Algebraic Stabilization of Linear Transformations in Artificial Neural Networks

Relevance of 3D Rotationally Equivariant Neural Networks for Predicting Protein-Ligand Binding Affinities

Future-oriented precision creation: recent advances in the intelligent design and synthesis of fine chemicals

Physical Constraint Frameworks in Chemistry: From Traditional Descriptors to Equivariant Neural Networks

No title available

An Intrusion Detection Method Based on Symmetric Federated Deep Learning in Complex Networks

Functions on Symmetric Matrices and Point Clouds via Lightweight Invariant Features from Galois Theory

Dielectric tensor of perovskite oxides at finite temperature using equivariant graph neural network potentials

Learning PDFs through interpretable latent representations in Mellin space

Acceleration of crystal structure relaxation with deep reinforcement learning

SuperMetal: a generative AI framework for rapid and precise metal ion location prediction in proteins

Artificial intelligence for science in quantum, atomistic, and continuum systems

Discovery of highly anisotropic dielectric crystals with equivariant graph neural networks

Equivariant neural network force fields for magnetic materials

Quantifying chemical short-range order in metallic alloys

Building an ab initio solvated DNA model using Euclidean neural networks

Predicting magnetic properties of van der Waals magnets using graph neural networks

Chemical-motif characterization of short-range order with E(3)-equivariant graph neural networks

A snapshot review on soft materials assembly design utilizing machine learning methods

Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview

Recent developments at the intersection of AI and theoretical physics

PharmRL: pharmacophore elucidation with deep geometric reinforcement learning

Filter

Filter

Article Lookup

Enter a citation