3 papers
q-bio.BM2025
DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules
Junjie Xu, Jiahao Zhang, Mangal Prakash +2
Geometric graph neural networks (GNNs) that respect E(3) symmetries have achieved strong performance on small molecule modeling, but they face scalability and expressiveness challe…
cs.LG2025
Geometric Hyena Networks for Large-scale Equivariant Learning
Artem Moskalev, Mangal Prakash, Junjie Xu +3
Processing global geometric context while preserving equivariance is crucial when modeling biological, chemical, and physical systems. Yet, this is challenging due to the computati…
q-bio.QM2025
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction
Junjie Xu, Artem Moskalev, Tommaso Mansi +2
Accurate prediction of RNA properties, such as stability and interactions, is crucial for advancing our understanding of biological processes and developing RNA-based therapeutics.…