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20242026
most citedComplete and Efficient Graph Transformers for Crystal Material Property Prediction

6 citations · 17 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.LG2026

Spin-Weighted Spherical Harmonics Enable Complete and Scalable -Equivariant Networks

Chenxing Liang, Yuchao Lin, Andrii Kryvenko +5

-equivariant networks are promising for 3D atomistic system modeling, yet their scalability is limited by the complexity of the Clebsch-Gordan Tensor Produc…

cs.LG2026

Orbital Transformers for Predicting Wavefunctions in Time-Dependent Density Functional Theory

Xuan Zhang, Haiyang Yu, Chengdong Wang +3

We aim to learn wavefunctions simulated by time-dependent density functional theory (TDDFT), which can be efficiently represented as linear combination coefficients of atomic orbit…

cs.LG2025

Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations

Yuchao Lin, Cong Fu, Zachary Krueger +6

-equivariant networks are the dominant models for machine learning interatomic potentials (MLIPs). The key operation of such networks is the Clebsch-Gordan (CG) tensor…

cs.LG2025

Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames

Haiyang Yu, Yuchao Lin, Xuan Zhang +2

We consider the task of predicting Hamiltonian matrices to accelerate electronic structure calculations, which plays an important role in physics, chemistry, and materials science.…

cs.LG2025★ 3 cited

A Materials Foundation Model via Hybrid Invariant-Equivariant Architectures

Keqiang Yan, Montgomery Bohde, Andrii Kryvenko +10

Machine learning interatomic potentials (MLIPs) can predict energy, force, and stress of materials and enable a wide range of downstream discovery tasks. A key design choice in MLI…

cs.LG2025★ 4 cited

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation

Keqiang Yan, Xiner Li, Hongyi Ling +8

We consider the problem of crystal materials generation using language models (LMs). A key step is to convert 3D crystal structures into 1D sequences to be processed by LMs. Prior…

cs.LG2024★ 6 cited

Complete and Efficient Graph Transformers for Crystal Material Property Prediction

Keqiang Yan, Cong Fu, Xiaofeng Qian +2

Crystal structures are characterized by atomic bases within a primitive unit cell that repeats along a regular lattice throughout 3D space. The periodic and infinite nature of crys…