Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Energy-based models (EBMs) show their efficiency in density estimation. However, MCMC sampling in traditional EBMs suffers from expensive computation. Although EBMs with minimax game avoid the above drawback, the energy estimation and generator's opt...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Convolutional neural networks (CNNs) are highly regarded for their ability to extract semantic information from visual inputs. However, this capability often leads to the inadvertent loss of important visual details. In this paper, we introduce an Ad...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Few-shot Knowledge Graph Completion (FKGC), an emerging technology capable of inferring new triples using only a few reference relation triples, has gained significant attention in recent years. However, existing FKGC methods primarily focus on struc...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Benefiting from the booming development of Transformer methods, the performance of lane detection tasks has been rapidly improved. However, due to the influence of inaccurate lane line shape constraints, the query sequences of existing transformer-ba...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
High-voltage defibrillation for eliminating cardiac spiral waves has significant side effects, necessitating the pursuit of low-energy alternatives for a long time. Adaptive optimization techniques and machine learning methods provide promising solut...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Convolutional neural networks (CNNs) can effectively extract local features, while Vision Transformer excels at capturing global features. Combining these two networks to enhance the classification performance of hyperspectral images (HSI) has garner...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Large Language Models (LLMs), which are trained on massive text data, have demonstrated remarkable advancements in language understanding capabilities. Nevertheless, it remains unclear to what extent LLMs have effectively captured and utilized the im...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Graph Neural Networks (GNNs) have been widely adopted to mine topological patterns contained in physiological signals for emotion recognition. However, since physiological signals are non-stationary and susceptible to various noises, there exists int...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Semi-supervised learning methods have wide applications thanks to the reasonable utilization for a part of label information of data. In recent years, non-negative matrix factorization (NMF) has received considerable attention because of its interpre...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Recently, cross-scene hyperspectral image classification(HSIC) via domain adaptation is drawing increasing attention. However, most existing methods either directly align the source domain and target domain without fully mining of SD information, or ...