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Found 4 papers, 1 papers with code
Atomas: Hierarchical Alignment on Molecule-Text for Unified Molecule Understanding and Generation
We design a Hierarchical Adaptive Alignment model to concurrently learn the fine-grained fragment correspondence between two modalities and align these representations of fragments in three levels.
Functional Protein Design with Local Domain Alignment
The core challenge of de novo protein design lies in creating proteins with specific functions or properties, guided by certain conditions.
DrugAssist: A Large Language Model for Molecule Optimization
Recently, the impressive performance of large language models (LLMs) on a wide range of tasks has attracted an increasing number of attempts to apply LLMs in drug discovery.
Multi-View Graph Neural Networks for Molecular Property Prediction
Guided by this observation, we present Multi-View Graph Neural Network (MV-GNN), a multi-view message passing architecture to enable more accurate predictions of molecular properties.
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