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Neural networks : the official journal of the International Neural Network Society
Apr 11, 2023
This paper explores a novel lifelong learning method with Shared and Private Latent Representations (SPLR), which are learned through synaptic intelligence. To solve a sequence of tasks, by considering the entire parameter learning trajectory, SPLR c...
Sensors (Basel, Switzerland)
Apr 7, 2023
Gait recognition, the task of identifying an individual based on their unique walking style, can be difficult because walking styles can be influenced by external factors such as clothing, viewing angle, and carrying conditions. To address these chal...
Nature neuroscience
Apr 6, 2023
Learning-to-learn, a progressive speedup of learning while solving a series of similar problems, represents a core process of knowledge acquisition that draws attention in both neuroscience and artificial intelligence. To investigate its underlying b...
Nature communications
Mar 31, 2023
Backpropagation is widely used to train artificial neural networks, but its relationship to synaptic plasticity in the brain is unknown. Some biological models of backpropagation rely on feedback projections that are symmetric with feedforward connec...
Attention, perception & psychophysics
Mar 28, 2023
Recently, Zhang et al. (Nature communications, 9(1), 3730, 2018) proposed an interesting model of attention guidance that uses visual features learnt by convolutional neural networks (CNNs) for object classification. I adapted this model for search e...
Anatomical sciences education
Mar 28, 2023
The integration of artificial intelligence (AI) into medical education has the potential to revolutionize the way students learn about biomedical sciences. Large language models, such as ChatGPT, can serve as virtual teaching assistants, providing st...
Neural networks : the official journal of the International Neural Network Society
Mar 27, 2023
Deep neural networks are enjoying unprecedented attention and success in recent years. However, catastrophic forgetting undermines the performance of deep models when the training data are arrived sequentially in an online multi-task learning fashion...
Medical teacher
Mar 27, 2023
BACKGROUND: The study aimed to evaluate the effectiveness of learning blood cell morphology by learning on our Artificial intelligence (AI)-based online platform.
Journal of chemical information and modeling
Mar 22, 2023
Retrosynthesis prediction, the task of identifying reactant molecules that can be used to synthesize product molecules, is a fundamental challenge in organic chemistry and related fields. To address this challenge, we propose a novel graph-to-graph t...
eLife
Mar 16, 2023
The predictive nature of the hippocampus is thought to be useful for memory-guided cognitive behaviors. Inspired by the reinforcement learning literature, this notion has been formalized as a predictive map called the successor representation (SR). T...