Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
The significant computational demands of Deep Neural Networks (DNNs) present a major challenge for their practical application. Recently, many Application-Specific Integrated Circuit (ASIC) chips have incorporated dedicated hardware support for neura...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Time series anomaly detection is crucial for maintaining stable systems. Existing methods face two main challenges. First, it is difficult to directly model the dependencies of diverse and complex patterns within the sequences. Second, many methods t...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Graph embedding aims to embed the information of graph data into low-dimensional representation space. Prior methods generally suffer from an imbalance of preserving structural information and node features due to their pre-defined inductive biases, ...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Recently, transformer-based methods have shown remarkable success in object re-identification. However, most works directly embed off-the-shelf transformer backbones for feature extraction. These methods treat all patch tokens equally, ignoring the d...
Journal of molecular graphics & modelling
Jul 1, 2025
Molecular representation learning facilitates multiple downstream tasks such as molecular property prediction (MPP) and drug design. Recent studies have shown great promise in applying self-supervised learning (SSL) to cope with the data scarcity in ...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
In practical engineering, many systems are required to operate under different constraint conditions due to considerations of system security. Violating these constraints conditions during operation may lead to performance degradation. Additionally, ...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Large language models (LLMs) roughly encode a sentence into a dense representation (a vector), which mixes up the semantic expression of all named entities within a sentence. So the decoding process is easily overwhelmed by sentence-specific informat...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
In this paper, we propose a novel neural architecture search (NAS) method called MAPOCNN, which leverages an enhanced version of the Artificial Protozoa Optimizer (APO) to optimize the architecture of Convolutional Neural Networks (CNNs). The APO is ...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Typical machine learning regression applications aim to report the mean or the median of the predictive probability distribution, via training with a squared or an absolute error scoring function. The importance of issuing predictions of more functio...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Previous asymmetric image retrieval methods based on knowledge distillation have primarily focused on aligning the global features of two networks to transfer global semantic information from the gallery network to the query network. However, these m...