AIMC Topic: Memory

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Estimating Scale-Invariant Future in Continuous Time.

Neural computation Feb 14, 2019
Natural learners must compute an estimate of future outcomes that follow from a stimulus in continuous time. Widely used reinforcement learning algorithms discretize continuous time and estimate either transition functions from one step to the next (...
Animals Models, Neurological Decision Making Machine Learning Brain Computer Simulation Reinforcement, Psychology Time Perception Anticipation, Psychological Humans Memory Models, Psychological Time
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Continual lifelong learning with neural networks: A review.

Neural networks : the official journal of the International Neural Network Society Feb 6, 2019
Humans and animals have the ability to continually acquire, fine-tune, and transfer knowledge and skills throughout their lifespan. This ability, referred to as lifelong learning, is mediated by a rich set of neurocognitive mechanisms that together c...
Neural Networks, Computer Machine Learning Animals Pattern Recognition, Automated Humans Memory
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Dreaming neural networks: Forgetting spurious memories and reinforcing pure ones.

Neural networks : the official journal of the International Neural Network Society Jan 29, 2019
The standard Hopfield model for associative neural networks accounts for biological Hebbian learning and acts as the harmonic oscillator for pattern recognition, however its maximal storage capacity is α∼0.14, far from the theoretical bound for symme...
Monte Carlo Method Memory Reinforcement, Psychology Neural Networks, Computer Algorithms Neuronal Plasticity
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Clone-Based Encoded Neural Networks to Design Efficient Associative Memories.

IEEE transactions on neural networks and learning systems Jan 28, 2019
In this paper, we introduce a neural network (NN) model named clone-based neural network (CbNN) to design associative memories. Neurons in CbNN can be cloned statically or dynamically which allows to increase the number of data that can be stored and...
Memory Humans Association Learning Neural Networks, Computer
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A small-world topology enhances the echo state property and signal propagation in reservoir computing.

Neural networks : the official journal of the International Neural Network Society Jan 16, 2019
Cortical neural connectivity has been shown to exhibit a small-world (SW) network topology. However, the role of the topology in neural information processing remains unclear. In this study, we investigated the learning performance of an echo state n...
Nonlinear Dynamics Connectome Memory Humans Neural Networks, Computer Brain
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Self-limited single nanowire systems combining all-in-one memristive and neuromorphic functionalities.

Nature communications Dec 4, 2018
The ability for artificially reproducing human brain type signals' processing is one of the main challenges in modern information technology, being one of the milestones for developing global communicating networks and artificial intelligence. Electr...
Synapses Silver Compounds Electrochemistry Memory Nanowires Volatilization Electronics Nanotechnology Biomimetics Zinc Oxide Electrodes Humans Neural Networks, Computer Neuronal Plasticity Brain Models, Neurological Equipment Design
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Perceptual Decision-Making: Biases in Post-Error Reaction Times Explained by Attractor Network Dynamics.

The Journal of neuroscience : the official journal of the Society for Neuroscience Nov 30, 2018
Perceptual decision-making is the subject of many experimental and theoretical studies. Most modeling analyses are based on statistical processes of accumulation of evidence. In contrast, very few works confront attractor network models' predictions ...
Reaction Time Computer Simulation Discrimination, Psychological Psychomotor Performance Neural Networks, Computer Synapses Models, Neurological Nonlinear Dynamics Algorithms Perception Decision Making Memory
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Concept learning through deep reinforcement learning with memory-augmented neural networks.

Neural networks : the official journal of the International Neural Network Society Nov 12, 2018
Deep neural networks have shown superior performance in many regimes to remember familiar patterns with large amounts of data. However, the standard supervised deep learning paradigm is still limited when facing the need to learn new concepts efficie...
Neural Networks, Computer Deep Learning Memory Humans Concept Formation Reinforcement, Psychology
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Neuroevolution of a Modular Memory-Augmented Neural Network for Deep Memory Problems.

Evolutionary computation Nov 8, 2018
We present Modular Memory Units (MMUs), a new class of memory-augmented neural network. MMU builds on the gated neural architecture of Gated Recurrent Units (GRUs) and Long Short Term Memory (LSTMs), to incorporate an external memory block, similar t...
Biological Evolution Models, Neurological Memory Neural Networks, Computer Algorithms Humans Deep Learning
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Multi-Source Ensemble Learning for the Remote Prediction of Parkinson's Disease in the Presence of Source-Wise Missing Data.

IEEE transactions on bio-medical engineering Nov 5, 2018
As the collection of mobile health data becomes pervasive, missing data can make large portions of datasets inaccessible for analysis. Missing data has shown particularly problematic for remotely diagnosing and monitoring Parkinson's disease (PD) usi...
Machine Learning Databases, Factual Female Aged Male Middle Aged Humans Neural Networks, Computer Memory Parkinson Disease Decision Making, Computer-Assisted Gait Memory and Learning Tests Telemedicine
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