AIMC Topic: Memory

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Temporal Contrastive Learning through implicit non-equilibrium memory.

Nature communications Mar 4, 2025
The backpropagation method has enabled transformative uses of neural networks. Alternatively, for energy-based models, local learning methods involving only nearby neurons offer benefits in terms of decentralized training, and allow for the possibili...
Neurons Memory Humans Neural Networks, Computer Feedback Models, Neurological Learning
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From materials to applications: a review of research on artificial olfactory memory.

Materials horizons Mar 4, 2025
Olfactory memory forms the basis for biological perception and environmental adaptation. Advancing artificial intelligence to replicate this biological perception as artificial olfactory memory is essential. The widespread use of various robotic syst...
Humans Artificial Intelligence Machine Learning Smell Olfactory Perception Memory Wearable Electronic Devices Robotics
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Memristor-based circuit design of interweaving mechanism of emotional memory in a hippocamp-brain emotion learning model.

Neural networks : the official journal of the International Neural Network Society Feb 13, 2025
Endowing robots with human-like emotional and cognitive abilities has garnered widespread attention, driving deep investigations into the complexities of these processes. However, few studies have examined the intricate circuits that govern the inter...
Emotions Models, Neurological Neural Networks, Computer Hippocampus Brain Robotics Humans Memory Learning
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Tuned Compositional Feature Replays for Efficient Stream Learning.

IEEE transactions on neural networks and learning systems Feb 6, 2025
Our brains extract durable, generalizable knowledge from transient experiences of the world. Artificial neural networks come nowhere close to this ability. When tasked with learning to classify objects by training on nonrepeating video frames in temp...
Algorithms Learning Memory Humans Neural Networks, Computer
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Memory-Dependent Computation and Learning in Spiking Neural Networks Through Hebbian Plasticity.

IEEE transactions on neural networks and learning systems Feb 6, 2025
Spiking neural networks (SNNs) are the basis for many energy-efficient neuromorphic hardware systems. While there has been substantial progress in SNN research, artificial SNNs still lack many capabilities of their biological counterparts. In biologi...
Machine Learning Computer Simulation Learning Humans Neural Networks, Computer Action Potentials Neurons Neuronal Plasticity Memory Models, Neurological
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Hybrid neural networks for continual learning inspired by corticohippocampal circuits.

Nature communications Feb 2, 2025
Current artificial systems suffer from catastrophic forgetting during continual learning, a limitation absent in biological systems. Biological mechanisms leverage the dual representation of specific and generalized memories within corticohippocampal...
Neurons Hippocampus Nerve Net Memory Cerebral Cortex Learning Animals Humans Models, Neurological Neural Networks, Computer
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Situation-Based Neuromorphic Memory in Spiking Neuron-Astrocyte Network.

IEEE transactions on neural networks and learning systems Jan 7, 2025
Mammalian brains operate in very special surroundings: to survive they have to react quickly and effectively to the pool of stimuli patterns previously recognized as danger. Many learning tasks often encountered by living organisms involve a specific...
Models, Neurological Action Potentials Neurons Nerve Net Astrocytes Neural Networks, Computer Computer Simulation Animals Humans Memory
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Pattern memory cannot be completely and truly realized in deep neural networks.

Scientific reports Dec 30, 2024
The unknown boundary issue, between superior computational capability of deep neural networks (DNNs) and human cognitive ability, has becoming crucial and foundational theoretical problem in AI evolution. Undoubtedly, DNN-empowered AI capability is i...
Cognition Humans Artificial Intelligence Memory Neural Networks, Computer Deep Learning
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H control for fractional order neural networks with uncertainties subject to deception attacks via Improved memory-event-triggered scheme and Its application.

Neural networks : the official journal of the International Neural Network Society Dec 28, 2024
The article discusses an improved memory-event-triggered strategy for H control class of fractional-order neural networks (FONNs) with uncertainties, which are vulnerable to deception attacks. The system under consideration is simultaneously influenc...
Computer Security Memory Uncertainty Algorithms Humans Deception Neural Networks, Computer
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A multi-memory-augmented network with a curvy metric method for video anomaly detection.

Neural networks : the official journal of the International Neural Network Society Dec 9, 2024
Anomaly detection task in video mainly refers to identifying anomalous events that do not conform to the learned normal patterns in the inferring phase. However, the Euclidean metric used in the learning and inferring phase by the most of the existin...
Memory Humans Deep Learning Neural Networks, Computer Video Recording Algorithms Pattern Recognition, Automated
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