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Found 4 papers, 0 papers with code
Diffusion-Driven Generative Framework for Molecular Conformation Prediction
The task of deducing three-dimensional molecular configurations from their two-dimensional graph representations holds paramount importance in the fields of computational chemistry and pharmaceutical development.
Domain Adaptive Graph Classification
Moreover, our approach incorporates adaptive perturbations into the dual branches, which align the source and target distribution to address domain discrepancies.
Dynamic Spiking Graph Neural Networks
Current work often uses SNNs instead of Recurrent Neural Networks (RNNs) by using binary features instead of continuous ones for efficient training, which would overlooks graph structure information and leads to the loss of details during propagation.
Just-in-Time Security Patch Detection -- LLM At the Rescue for Data Augmentation
To address this pressing issue, we introduce a novel security patch detection system, LLMDA, which capitalizes on Large Language Models (LLMs) and code-text alignment methodologies for patch review, data enhancement, and feature combination.
