AIMC Topic: Learning

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Delay learning based on temporal coding in Spiking Neural Networks.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNNs) hold great potential for mimicking the brain's efficient processing of information. Although biological evidence suggests that precise spike timing is crucial for effective information encoding, contemporary SNN researc...

Advanced technologies and mathematical metacognition: The present and future orientation.

Bio Systems
The intersection of mathematical cognition, metacognition, and advanced technologies presents a frontier with profound implications for human learning and artificial intelligence. This paper traces the historical roots of these concepts from the Pyth...

Neuromorphic learning and recognition in WOthin film-based forming-free flexible electronic synapses.

Nanotechnology
In pursuing advanced neuromorphic applications, this study introduces the successful engineering of a flexible electronic synapse based on WO, structured as W/WO/Pt/Muscovite-Mica. This artificial synapse is designed to emulate crucial learning behav...

Active inference goes to school: the importance of active learning in the age of large language models.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Human learning essentially involves embodied interactions with the material world. But our worlds now include increasing numbers of powerful and (apparently) disembodied generative artificial intelligence (AI). In what follows we ask how best to unde...

Artificial intelligence tools utilized in nursing education: Incidence and associated factors.

Nurse education today
BACKGROUND: Artificial intelligence technology is among the most significant advancements that provide students with effective learning opportunities in this digital era. Therefore, the National League for Nursing states that it is necessary to refra...

Exploring the effectiveness of reward-based learning strategies for second-language speech sounds.

Psychonomic bulletin & review
Adults struggle to learn non-native speech categories in many experimental settings (Goto, Neuropsychologia, 9(3), 317-323 1971), but learn efficiently in a video game paradigm where non-native speech sounds have functional significance (Lim & Holt, ...

Repetitive Impedance Learning-Based Physically Human-Robot Interactive Control.

IEEE transactions on neural networks and learning systems
Model-based impedance learning control can provide variable impedance regulation for robots through online impedance learning without interaction force sensing. However, the existing related results only guarantee the closed-loop control systems to b...

Towards a rigorous analysis of mutual information in contrastive learning.

Neural networks : the official journal of the International Neural Network Society
Contrastive learning has emerged as a cornerstone in unsupervised representation learning. Its primary paradigm involves an instance discrimination task utilizing InfoNCE loss where the loss has been proven to be a form of mutual information. Consequ...

Emergence and reconfiguration of modular structure for artificial neural networks during continual familiarity detection.

Science advances
Advances in artificial intelligence enable neural networks to learn a wide variety of tasks, yet our understanding of the learning dynamics of these networks remains limited. Here, we study the temporal dynamics during learning of Hebbian feedforward...