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Zhiming Yang

2 accepted papers

2024

Extracting Training Data from Molecular Pre-trained Models

NeurIPS 2024poster

Graph Neural Networks (GNNs) have significantly advanced the field of drug discovery, enhancing the speed and efficiency of molecular identification. However, training these GNNs demands vast amounts of molecular data, which has spurred the emergence of collaborative model-sharing initiatives. These…

2024

Measuring Task Similarity and Its Implication in Fine-Tuning Graph Neural Networks

AAAI 2024technical

The paradigm of pre-training and fine-tuning graph neural networks has attracted wide research attention. In previous studies, the pre-trained models are viewed as universally versatile, and applied for a diverse range of downstream tasks. In many situations, however, this practice results in limite…