Similarity-based domain adaptation networkMeixin Peng a bZhanshan Li a bXin Juan c
Therefore, this paper proposes a Similarity-Based Adaptation Network (SBAN), which optimizes Similarity-Based Domain Discrepancy (SBDD) that models similarity-based intra-domain and inter-domain discrepancies, and pro -poses an alternating update strategy to train the SBAN. Specifically, we assign ...
memory (LSTM) to get a better representation of protein and compound. DeepCDA encodes the binding strength by utilizing a two-sided attention mechanism and tries to improve the generalization ability by utilizing a domain adaptation technique. In this paper, we propose a similarity-based model to ...
27 used gradient-based SIMP together and a Generative Adversarial Network (GAN) for design exploration with an additional design novelty objective, interpreted as geometric dissimilarity. This methodology, however, requires an expensive generation of large amounts of design concepts using TO in order ...
Urban transportation networks often exhibit different network structures based on the goals of network designers. For instance, some networks focus on connecting people living in the outer layers of the city to the city core, while others prefer to develop a robust infrastructure servicing the core19...
we introduce a complete framework of social network data processing for emergency event detection, which integrates classification and attribute information extraction to define the similarity between two posts, and then propose a new dynamical text clustering algorithm based on the similarity, and such ...
Image-based agents rely on models that are pre-trained on image data. These models learn image features, object recognition, scene understanding, and more, primarily using the Convolutional Neural Network (CNN) architecture, such as Residual Network (ResNet) or Efficient Neural Network (EfficientNet...
And the introduction of the bidirectional recurrent neural network aims to discover the evolution pattern of students’ ability and knowledge structure over time. Specifically, the goal of the model is to predict students’ performance in the next semester by using their previous course performance. ...
Note, however, that it is unclear whether sustained activity in all of these areas is produced locally, or if it results from multi-regional interactions (see23 for consideration of local circuit and large-scale network mechanisms that could support sustained activation). Our model is agnostic on...
A classification and recognition algorithm of key figures in public opinion integrating multidimensional similarity and K-shell based on supernetwork Guanghui Wang, Yushan Wang, Kaidi Liu & Shu Sun Humanities and Social Sciences Communications volume 11, Article number: 262 (2024) Cite this article ...