Many computational methods have been proposed to predict drug–drug interactions (DDIs), which can occur when combining drugs to treat various diseases, but most mainly utilize single-source features ...

A vision encoder is a necessary component for allowing many leading LLMs to be able to work with images uploaded by users.

Please cite our work if you like or are using our codes for your projects! Kun Xu, Lingfei Wu, Zhiguo Wang, Yansong Feng, Michael Witbrock, and Vadim Sheinin (first and second authors contributed ...

In conclusion, Hi-GMAE represents a significant advancement in self-supervised graph pre-training. By integrating multi-scale coarsening, an innovative masking strategy, and a hierarchical ...

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This model is divided into two parts, encoder and decoder. input of encoder is image tensor. shape is [1,3,192,640]. output is list of five tensors. input of decoder is output of encoder and when i ...

This graph representation of ligand binding sites was used to accurately classify pockets in protein structures with GraphSite (Shi et al., 2021). Encoder-Decoder Architecture. Pocket2Drug is ...

Building an Encoder-Decoder with LSTM layers for Time-Series forecasting . ... Here we can see the performance of the model which is quite satisfactory and we can see in the graph also how the slope ...