AIMC Topic: Memory

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Uncovering memorization effect in the presence of spurious correlations.

Nature communications Jul 1, 2025
Machine learning models often rely on simple spurious features - patterns in training data that correlate with targets but are not causally related to them, like image backgrounds in foreground classification. This reliance typically leads to imbalan...
Machine Learning Neurons Memory Humans Neural Networks, Computer
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Neuro-symbolic procedural semantics for explainable visual dialogue.

PloS one May 27, 2025
This paper introduces a novel approach to visual dialogue that is based on neuro-symbolic procedural semantics. The approach builds further on earlier work on procedural semantics for visual question answering and expands it with neuro-symbolic mecha...
Semantics Memory Artificial Intelligence Communication Humans
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Neuron-astrocyte associative memory.

Proceedings of the National Academy of Sciences of the United States of America May 23, 2025
Astrocytes, the most abundant type of glial cell, play a fundamental role in memory. Despite most hippocampal synapses being contacted by an astrocyte, there are no current theories that explain how neurons, synapses, and astrocytes might collectivel...
Models, Neurological Humans Neurons Astrocytes Animals Synapses Hippocampus Memory
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Cortical-subcortical neural networks for motor learning and storing sequence memory.

Neural networks : the official journal of the International Neural Network Society May 7, 2025
Motor sequence learning relies on the synergistic collaboration of multiple brain regions. However, most existing models for motor sequence learning primarily focus on functional-level analyses of sequence memory mechanisms, providing limited neuroph...
Memory, Short-Term Neurons Prefrontal Cortex Models, Neurological Nerve Net Memory Thalamus Cerebral Cortex Neural Pathways Neural Networks, Computer Learning Humans
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Neural Network Circuits for Bionic Associative Memory and Temporal Order Memory Based on DNA Strand Displacement.

IEEE transactions on neural networks and learning systems May 2, 2025
Pavlovian associative memory plays an important role in our daily life and work. The realization of Pavlovian associative memory at the deoxyribonucleic acid (DNA) molecular level will promote the development of biological computing and broaden the a...
Neural Networks, Computer Computer Simulation Memory Bionics DNA Humans
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Research on memory failure prediction based on ensemble learning.

PloS one Apr 23, 2025
Timely prediction of memory failures is crucial for the stable operation of data centers. However, existing methods often rely on a single classifier, which can lead to inaccurate or unstable predictions. To address this, we propose a new ensemble mo...
Humans Algorithms Machine Learning Models, Theoretical Memory Ensemble Learning
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Design and Implementation of Pavlovian Associative Memory Based on DNA Neurons.

IEEE transactions on neural networks and learning systems Apr 4, 2025
In the field of biocomputing and neural networks, deoxyribonucleic acid (DNA) strand displacement (DSD) technology performs well in computation, programming, and information processing. In this article, the multiplication gate, addition gate, and thr...
Association Learning Memory Neural Networks, Computer Humans Conditioning, Classical Computer Simulation DNA Animals Neurons
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Scalable Multi-FPGA HPC Architecture for Associative Memory System.

IEEE transactions on biomedical circuits and systems Apr 2, 2025
Associative memory is a cornerstone of cognitive intelligence within the human brain. The Bayesian confidence propagation neural network (BCPNN), a cortex-inspired model with high biological plausibility, has proven effective in emulating high-level ...
Memory Humans Models, Neurological Neural Networks, Computer Bayes Theorem Algorithms
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Studying memory narratives with natural language processing.

Trends in cognitive sciences Mar 19, 2025
Cognitive neuroscience research has begun to use natural language processing (NLP) to examine memory narratives with the hopes of gaining a nuanced understanding of the mechanisms underlying differences in memory recall, both across groups and tasks....
Memory Mental Recall Natural Language Processing Cognitive Neuroscience Humans Narration
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A general framework for interpretable neural learning based on local information-theoretic goal functions.

Proceedings of the National Academy of Sciences of the United States of America Mar 5, 2025
Despite the impressive performance of biological and artificial networks, an intuitive understanding of how their local learning dynamics contribute to network-level task solutions remains a challenge to this date. Efforts to bring learning to a more...
Models, Neurological Humans Algorithms Memory Neurons Neural Networks, Computer Learning Information Theory
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