Neural networks : the official journal of the International Neural Network Society
Jan 22, 2025
Learning from data streams that emerge from nonstationary environments has many real-world applications and poses various challenges. A key characteristic of such a task is the varying nature of the underlying data distributions over time (concept dr...
Journal of computational neuroscience
Jan 22, 2025
Hippocampal representations of space and time seem to share a common coding scheme characterized by neurons with bell-shaped tuning curves called place and time cells. The properties of the tuning curves are consistent with Weber's law, such that, in...
Artificial neural networks (ANNs) are at the core of most Deep Learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and natural language processing. However, unlike biological brains who tackl...
Humans excel at applying learned behavior to unlearned situations. A crucial component of this generalization behavior is our ability to compose/decompose a whole into reusable parts, an attribute known as compositionality. One of the fundamental que...
Neural networks : the official journal of the International Neural Network Society
Jan 21, 2025
This paper proposes a new continual learning method with Bayesian Compression for Shared and Private Latent Representations (BCSPLR), which learns a compact model structure while preserving the accuracy. In Shared and Private Latent Representations (...
Neural networks : the official journal of the International Neural Network Society
Jan 15, 2025
Artificial Neural Networks (ANNs) aim at mimicking information processing in biological networks. In cognitive neuroscience, graph modeling is a powerful framework widely used to study brain structural and functional connectivity. Yet, the extension ...
Humans and animals have a striking ability to learn relationships between items in experience (such as stimuli, objects and events), enabling structured generalization and rapid assimilation of new information. A fundamental type of such relational l...
For trained individuals such as athletes and musicians, learning often plateaus after extensive training, known as the "ceiling effect." One bottleneck to overcome it is having no prior physical experience with the skill to be learned. Here, we chall...
Student performance is crucial for addressing learning process problems and is also an important factor in measuring learning outcomes. The ability to improve educational systems using data knowledge has driven the development of the field of educati...
BACKGROUND: Artificial intelligence has gradually been used into various fields of medical education at present. Under the background of moxibustion robot teaching assistance, the study aims to explore the relationship and the internal mechanism betw...
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