AIMC Topic: Mental Recall

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Online continual learning with declarative memory.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks are enjoying unprecedented attention and success in recent years. However, catastrophic forgetting undermines the performance of deep models when the training data are arrived sequentially in an online multi-task learning fashion...

Associative memory of structured knowledge.

Scientific reports
A long standing challenge in biological and artificial intelligence is to understand how new knowledge can be constructed from known building blocks in a way that is amenable for computation by neuronal circuits. Here we focus on the task of storage ...

Audit lead selection and yield prediction from historical tax data using artificial neural networks.

PloS one
Tax audits are a crucial process adopted in all tax departments to ensure tax compliance and fairness. Traditionally, tax audit leads have been selected based on empirical rules and randomization methods, which are not adaptive, may miss major cases ...

Hybrid-Enhanced Siamese Similarity Models in Ligand-Based Virtual Screen.

Biomolecules
Information technology has become an integral aspect of the drug development process. The virtual screening process (VS) is a computational technique for screening chemical compounds in a reasonable amount of time and cost. The similarity search is o...

Integration of Neighbor Topologies Based on Meta-Paths and Node Attributes for Predicting Drug-Related Diseases.

International journal of molecular sciences
Identifying new disease indications for existing drugs can help facilitate drug development and reduce development cost. The previous drug-disease association prediction methods focused on data about drugs and diseases from multiple sources. However,...

A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.

Nutrients
BACKGROUND: Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration pneumonia. This study aimed to develop a simple screening test using image recognition with a low r...

Incremental Concept Learning via Online Generative Memory Recall.

IEEE transactions on neural networks and learning systems
The ability to learn more concepts from incrementally arriving data over time is essential for the development of a lifelong learning system. However, deep neural networks often suffer from forgetting previously learned concepts when continually lear...

The current state of memory Specificity Training (MeST) for emotional disorders.

Current opinion in psychology
Memory Specificity Training (MeST) is an intervention developed from basic science that has found clinical utility. MeST uses cued recall exercises to target the difficulty that some people with emotional disorders have in recalling personally experi...

NMDA Receptor Alterations After Mild Traumatic Brain Injury Induce Deficits in Memory Acquisition and Recall.

Neural computation
Mild traumatic brain injury (mTBI) presents a significant health concern with potential persisting deficits that can last decades. Although a growing body of literature improves our understanding of the brain network response and corresponding underl...

Image memorability is predicted by discriminability and similarity in different stages of a convolutional neural network.

Learning & memory (Cold Spring Harbor, N.Y.)
The features of an image can be represented at multiple levels-from its low-level visual properties to high-level meaning. What drives some images to be memorable while others are forgettable? We address this question across two behavioral experiment...