Proceedings of the National Academy of Sciences of the United States of America
Jun 27, 2022
Understanding how the brain learns throughout a lifetime remains a long-standing challenge. In artificial neural networks (ANNs), incorporating novel information too rapidly results in catastrophic interference, i.e., abrupt loss of previously acquir...
Sensors (Basel, Switzerland)
Jun 26, 2022
The availability of educational data obtained by technology-assisted learning platforms can potentially be used to mine student behavior in order to address their problems and enhance the learning process. Educational data mining provides insights fo...
Journal of computational biology : a journal of computational molecular cell biology
Jun 24, 2022
Coordinated hunting is widely observed in animals, and sharing rewards is often considered a major incentive for its success. While current theories about the role played by sharing in coordinated hunting are based on correlational evidence, we revea...
Scientific reports
Jun 24, 2022
The work of McCloskey and Cohen popularized the concept of catastrophic interference. They used a neural network that tried to learn addition using two groups of examples as two different tasks. In their case, learning the second task rapidly deterio...
Computational intelligence and neuroscience
Jun 24, 2022
The objectives are to solve many problems in traditional English reading teaching, such as the passive acceptance of students' learning situation, the rigid teaching mode of teachers and the difficulty in taking into account the individual needs of e...
PLoS computational biology
Jun 21, 2022
Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervi...
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Jun 20, 2022
We propose the GENERIC formalism informed neural networks (GFINNs) that obey the symmetric degeneracy conditions of the GENERIC formalism. GFINNs comprise two modules, each of which contains two components. We model each component using a neural netw...
Sensors (Basel, Switzerland)
Jun 18, 2022
Object detection is one of the most important and challenging branches of computer vision. It has been widely used in people's lives, such as for surveillance security and autonomous driving. We propose a novel dual-path multi-scale object detection ...
Medical image analysis
Jun 17, 2022
Disentangled representation learning has been proposed as an approach to learning general representations even in the absence of, or with limited, supervision. A good general representation can be fine-tuned for new target tasks using modest amounts ...
Computational intelligence and neuroscience
Jun 17, 2022
In this paper, we use a particle swarm optimization neural network algorithm to analyze the teaching data of physical education faculties and evaluate the quality of teaching in physical education faculties. By studying and analyzing the optimization...