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It is proved that the Hypergraph Neural Network, an invariant architecture with 3-body message passing, is a universal approximator for potential energy surfaces and provides the first rigorous justification for the common practice of using multi-layer message passing with a per-layer cutoff smaller than the physical i...
PopPert predicts perturbation-induced changes in distribution parameters, eliminating the need for cell-level correspondence and reducing sensitivity to single-cell noise, establishing population-level joint distribution learning as an effective paradigm for predicting transcriptional responses from unpaired single-cel...
This work introduces a symmetric dual-path architecture that both leverages PLMs for pretrained sequence evolution knowledge and MPLMs for pretrained structural knowledge to iteratively guide protein sequence generation.
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