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20102026
most citedE(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials

1.9k citations · 4k across the 54 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

cs.LG2023★ 4 cited

Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for 3D Molecule Generation

Ameya Daigavane, Song Kim, Mario Geiger +1

We present Symphony, an -equivariant autoregressive generative model for 3D molecular geometries that iteratively builds a molecule from molecular fragments. Existing autoreg…

cond-mat.mtrl-sci2023★ 1 cited

Quantifying chemical short-range order in metallic alloys

Killian Sheriff, Yifan Cao, Tess Smidt +1

Metallic alloys often form phases - known as solid solutions - in which chemical elements are spread out on the same crystal lattice in an almost random manner. The tendency of cer…

cs.LG2023★ 2 cited

Ophiuchus: Scalable Modeling of Protein Structures through Hierarchical Coarse-graining SO(3)-Equivariant Autoencoders

Allan dos Santos Costa, Ilan Mitnikov, Mario Geiger +3

Three-dimensional native states of natural proteins display recurring and hierarchical patterns. Yet, traditional graph-based modeling of protein structures is often limited to ope…

cs.LG2023

Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution

Rui Wang, Elyssa Hofgard, Han Gao +2

Modeling symmetry breaking is essential for understanding the fundamental changes in the behaviors and properties of physical systems, from microscopic particle interactions to mac…

cs.LG2023★ 16 cited

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Xuan Zhang, Limei Wang, Jacob Helwig +60

Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating…

cs.LG2023★ 88 cited

EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Yi-Lun Liao, Brandon Wood, Abhishek Das +1

Equivariant Transformers such as Equiformer have demonstrated the efficacy of applying Transformers to the domain of 3D atomistic systems. However, they are limited to small degree…

stat.ML2023★ 2 cited

A General Framework for Equivariant Neural Networks on Reductive Lie Groups

Ilyes Batatia, Mario Geiger, Jose Munoz +3

Reductive Lie Groups, such as the orthogonal groups, the Lorentz group, or the unitary groups, play essential roles across scientific fields as diverse as high energy physics, quan…