WiMi also plans to combine the attentional autoencoder network with other advanced recommendation technologies to further enhance recommendation effectiveness.

On the basis of the extracted cancer risk variables, a deep learning model was developed for BRISK to aid in predicting malignancy. Figure 2 illustrates a schematic diagram of the model, which ...

The team proposed a novel representation learning method based on serial autoencoders for personalized recommendation.

Deep learning is utilized in WiMi's deep learning-based multi-view hybrid recommendation system for feature learning and recommendation model construction.

Dynamic Yield’s Deep Learning-Based Recommendations instantly identify intent, even from the first session, to automatically match customers with the products they are most interested in or ...

Jianwei Shuai's team and Jiahuai Han's team at Xiamen University have developed a deep autoencoder-based data-independent acquisition data analysis software for protein mass spectrometry, which ...

WiMi's attentional autoencoder network is a technical framework for efficient recommendation systems that combine autoencoders and attention mechanisms to improve the accuracy and efficiency of ...