Neural networks : the official journal of the International Neural Network Society
Sep 24, 2023
Split learning, a distributed learning framework, has garnered significant attention from academic and industrial communities. In contrast to federated learning, split learning offers a more flexible architecture for participants with limited computi...
Journal of the neurological sciences
Sep 15, 2023
BACKGROUND AND OBJECTIVES: This is an observational study of the performance of an artificial intelligence-powered chatbot tasked with solving unknown neurologic case vignettes. The primary objective of the study is to assess the current capabilities...
Neural networks : the official journal of the International Neural Network Society
Sep 14, 2023
Contact torque sensing allows robot manipulators to cooperate with humans and detect accidental collisions in real time to ensure safety. Most sensorless torque estimation schemes, which are based on linear observer approaches, cannot compromise betw...
Current opinion in neurobiology
Sep 12, 2023
While neural plasticity has long been studied as the basis of learning, the growth of large-scale neural recording techniques provides a unique opportunity to study how learning-induced activity changes are coordinated across neurons within the same ...
Neural networks : the official journal of the International Neural Network Society
Sep 12, 2023
Graph convolutional network has been extensively employed in semi-supervised classification tasks. Although some studies have attempted to leverage graph convolutional networks to explore multi-view data, they mostly consider the fusion of feature an...
The British journal of radiology
Sep 12, 2023
Various forms of artificial intelligence (AI) applications are being deployed and used in many healthcare systems. As the use of these applications increases, we are learning the failures of these models and how they can perpetuate bias. With these n...
Journal of experimental psychology. General
Sep 11, 2023
Humans are particularly sensitive to relationships between parts of objects. It remains unclear why this is. One hypothesis is that relational features are highly diagnostic of object categories and emerge as a result of learning to classify objects....
Neural networks : the official journal of the International Neural Network Society
Sep 11, 2023
Contrastive learning methods aim to learn shared representations by minimizing distances between positive pairs, and maximizing distances between negative pairs in the embedding space. To achieve better performance of contrastive learning, one of the...
Neural networks : the official journal of the International Neural Network Society
Sep 11, 2023
We introduce Tadam (Trust region ADAptive Moment estimation), a new optimizer based on the trust region of the second-order approximation of the loss using the Fisher information matrix. Despite the enhanced gradient estimations offered by second-ord...
Biological cybernetics
Sep 11, 2023
The precise timing of spikes emitted by neurons plays a crucial role in shaping the response of efferent biological neurons. This temporal dimension of neural activity holds significant importance in understanding information processing in neurobiolo...