AIMC Topic: Learning

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Deep neural networks and humans both benefit from compositional language structure.

Nature communications Dec 30, 2024
Deep neural networks drive the success of natural language processing. A fundamental property of language is its compositional structure, allowing humans to systematically produce forms for new meanings. For humans, languages with more compositional ...
Natural Language Processing Humans Linguistics Neural Networks, Computer Learning Language Deep Learning
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Unified Knowledge-Guided Molecular Graph Encoder with multimodal fusion and multi-task learning.

Neural networks : the official journal of the International Neural Network Society Dec 24, 2024
The remarkable success of Graph Neural Networks underscores their formidable capacity to assimilate multimodal inputs, markedly enhancing performance across a broad spectrum of domains. In the context of molecular modeling, considerable efforts have ...
Models, Molecular Humans Machine Learning Learning Neural Networks, Computer
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Enhancing consistency and mitigating bias: A data replay approach for incremental learning.

Neural networks : the official journal of the International Neural Network Society Dec 20, 2024
Deep learning systems are prone to catastrophic forgetting when learning from a sequence of tasks, as old data from previous tasks is unavailable when learning a new task. To address this, some methods propose replaying data from previous tasks durin...
Humans Neural Networks, Computer Deep Learning Bias Learning
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An Artificial Neural Network for Image Classification Inspired by the Aversive Olfactory Learning Neural Circuit in Caenorhabditis elegans.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Dec 16, 2024
This study introduces an artificial neural network (ANN) for image classification task, inspired by the aversive olfactory learning neural circuit in Caenorhabditis elegans (C. elegans). Although artificial neural networks (ANNs) have demonstrated re...
Neural Networks, Computer Caenorhabditis elegans Smell Nerve Net Learning Animals
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Hybrid SEM-ANN model for predicting undergraduates' e-learning continuance intention based on perceived educational and emotional support.

PloS one Dec 13, 2024
Based on the Expectation Confirmation Model (ECM), this study explores the impact of perceived educational and emotional support on university students' continuance intention to engage in e-learning. Researchers conducted a survey using structured qu...
Universities Emotions Surveys and Questionnaires Young Adult Adolescent Learning Intention Adult Male Humans Female Education, Distance Students Neural Networks, Computer
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Similarity-based context aware continual learning for spiking neural networks.

Neural networks : the official journal of the International Neural Network Society Dec 12, 2024
Biological brains have the capability to adaptively coordinate relevant neuronal populations based on the task context to learn continuously changing tasks in real-world environments. However, existing spiking neural network-based continual learning ...
Neurons Models, Neurological Action Potentials Humans Algorithms Learning Neural Networks, Computer
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Neurocontrol for fixed-length trajectories in environments with soft barriers.

Neural networks : the official journal of the International Neural Network Society Dec 12, 2024
In this paper we present three neurocontrol problems where the analytic policy gradient via back-propagation through time is used to train a simulated agent to maximise a polynomial reward function in a simulated environment. If the environment inclu...
Environment Neural Networks, Computer Algorithms Learning Reward Computer Simulation Humans
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Counterfactual learning for higher-order relation prediction in heterogeneous information networks.

Neural networks : the official journal of the International Neural Network Society Dec 10, 2024
Heterogeneous Information Networks (HINs) play a crucial role in modeling complex social systems, where predicting missing links/relations is a significant task. Existing methods primarily focus on pairwise relations, but real-world scenarios often i...
Humans Machine Learning Learning Neural Networks, Computer
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3D-BCLAM: A Lightweight Neurodynamic Model for Assessing Student Learning Effectiveness.

Sensors (Basel, Switzerland) Dec 9, 2024
Evaluating students' learning effectiveness is of great importance for gaining a deeper understanding of the learning process, accurately diagnosing learning barriers, and developing effective teaching strategies. Emotion, as a key factor influencing...
Neural Networks, Computer Machine Learning Humans Deep Learning Emotions Learning Students
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Stabilizing sequence learning in stochastic spiking networks with GABA-Modulated STDP.

Neural networks : the official journal of the International Neural Network Society Dec 7, 2024
Cortical networks are capable of unsupervised learning and spontaneous replay of complex temporal sequences. Endowing artificial spiking neural networks with similar learning abilities remains a challenge. In particular, it is unresolved how differen...
Learning Neurons Neuronal Plasticity Models, Neurological gamma-Aminobutyric Acid Humans Action Potentials Stochastic Processes Neural Networks, Computer
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