Neural networks : the official journal of the International Neural Network Society
Feb 11, 2025
Scientific entity relation extraction intends to promote the performance of each subtask through exploring the contextual representations with rich scientific semantics. However, most of existing models encounter the dilemma of scientific semantic di...
Neural networks : the official journal of the International Neural Network Society
Feb 11, 2025
Recent advances in the design of convolutional neural networks have shown that performance can be enhanced by improving the ability to represent multi-scale features. However, most existing methods either focus on designing more sophisticated attenti...
Neural networks : the official journal of the International Neural Network Society
Feb 10, 2025
For unknown nonlinear systems with state constraints, it is difficult to achieve the safe optimal control by using Q-learning methods based on traditional quadratic utility functions. To solve this problem, this article proposes an accelerated safe Q...
Neural networks : the official journal of the International Neural Network Society
Feb 10, 2025
Most few-shot object detection methods aim to utilize the learned generalizable knowledge from base categories to identify instances of novel categories. The fundamental assumption of these approaches is that the model can acquire sufficient transfer...
Neural networks : the official journal of the International Neural Network Society
Feb 10, 2025
3D dense captioning (3D-DC) transcends traditional 2D image captioning by requiring detailed spatial understanding and object localization, aiming to generate high-quality descriptions for objects within 3D environments. Current approaches struggle w...
Neural networks : the official journal of the International Neural Network Society
Feb 8, 2025
Hierarchical predictive coding (hPC) provides a compelling framework for understanding how the cortex predicts future sensory inputs by minimizing prediction errors through an internal generative model of the external world. Existing deep learning mo...
Neural networks : the official journal of the International Neural Network Society
Feb 8, 2025
Transformer-based vision models are often assumed to have an advantage over traditional convolutional neural networks (CNNs) due to their ability to model long-range dependencies and interactions between inputs. However, the remarkable success of pur...
Neural networks : the official journal of the International Neural Network Society
Feb 8, 2025
Long-tailed classification is a significant yet challenging vision task that aims to making the clearest decision boundaries via integrating semantic consistency and texture characteristics. Unlike prior methods, we design spatial constraint sampling...
Neural networks : the official journal of the International Neural Network Society
Feb 8, 2025
In model-based reinforcement learning (RL) approaches, the estimated model of a real environment is learned with limited data and then utilized for policy optimization. As a result, the policy optimization process in model-based RL is influenced by b...
Neural networks : the official journal of the International Neural Network Society
Feb 7, 2025
Recent developments on deep learning established some theoretical properties of deep neural networks estimators. However, most of the existing works on this topic are restricted to bounded loss functions or (sub)-Gaussian or bounded variables. This p...