Is Distance Matrix Enough for Geometric Deep Learning?

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Is Distance Matrix Enough for Geometric Deep Learning?

Neural Information Processing Systems (NeurIPS), 2023

11 February 2023

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Papers citing "Is Distance Matrix Enough for Geometric Deep Learning?"

11 / 11 papers shown

Title
Toward bilipshiz geometric models Yonatan Sverdlov Eitan Rosen Nadav Dym 3DPC 72 0 0 13 Nov 2025
Geometric Mixture Models for Electrolyte Conductivity Prediction Anyi Li Jiacheng Cen Songyou Li Mingze Li Yang Yu Wenbing Huang 132 1 0 17 Oct 2025
Universally Invariant Learning in Equivariant GNNs Jiacheng Cen Anyi Li Ning Lin Tingyang Xu Yu Rong Deli Zhao Zihe Wang Wenbing Huang 116 1 0 15 Oct 2025
GeoRecon: Graph-Level Representation Learning for 3D Molecules via Reconstruction-Based Pretraining Shaoheng Yan Zian Li Muhan Zhang AI4CE 166 2 0 16 Jun 2025
Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?Neural Information Processing Systems (NeurIPS), 2024 Jiacheng Cen Anyi Li Ning Lin Yuxiang Ren Zihe Wang Wenbing Huang 347 16 0 15 Oct 2024
Geometric Representation Condition Improves Equivariant Molecule Generation Zian Li Cai Zhou Xiyuan Wang Xingang Peng Muhan Zhang 411 6 0 04 Oct 2024
On the Expressive Power of Sparse Geometric MPNNs Yonatan Sverdlov Nadav Dym 446 5 0 02 Jul 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 282 7 0 07 Feb 2024
On dimensionality of feature vectors in MPNNsInternational Conference on Machine Learning (ICML), 2024 César Bravo Chris Köcher Cristóbal Rojas 127 8 0 06 Feb 2024
Weisfeiler Leman for Euclidean Equivariant Machine Learning Snir Hordan Tal Amir Nadav Dym 244 10 0 04 Feb 2024
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness TheoremNeural Information Processing Systems (NeurIPS), 2023 Tal Amir S. Gortler Ilai Avni Ravi Ravina Nadav Dym 226 31 0 10 Jun 2023