AIMC Topic: Learning

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Dynamic mutual predictions during social learning: A computational and interbrain model.

Neuroscience and biobehavioral reviews
During social interactions, we constantly learn about the thoughts, feelings, and personality traits of our interaction partners. Learning in social interactions is critical for bond formation and acquiring knowledge. Importantly, this type of learni...

AI is transforming how science is done. Science education must reflect this change.

Science (New York, N.Y.)
There is growing interest in the use of artificial intelligence (AI) in science education. Many issues and questions raised about the role of AI in science education target primarily science learning objectives. They relate to AI's capacity to genera...

Artificial Tactile Perception System Based on Spiking Tactile Neurons and Spiking Neural Networks.

ACS applied materials & interfaces
The artificial tactile perception system of this work utilizes a fully connected spiking neural network (SNN) comprising two layers. Its architecture is streamlined and energy-efficient as it directly integrates spiking tactile neurons with piezoresi...

Enhancing domain generalization in the AI-based analysis of chest radiographs with federated learning.

Scientific reports
Developing robust artificial intelligence (AI) models that generalize well to unseen datasets is challenging and usually requires large and variable datasets, preferably from multiple institutions. In federated learning (FL), a model is trained colla...

Considering the Secondary Use of Clinical and Educational Data to Facilitate the Development of Artificial Intelligence Models.

Academic medicine : journal of the Association of American Medical Colleges
Medical training programs and health care systems collect ever-increasing amounts of educational and clinical data. These data are collected with the primary purpose of supporting either trainee learning or patient care. Well-established principles g...

Meta-structure-based graph attention networks.

Neural networks : the official journal of the International Neural Network Society
Due to the ubiquity of graph-structured data, Graph Neural Network (GNN) have been widely used in different tasks and domains and good results have been achieved in tasks such as node classification and link prediction. However, there are still many ...

Phar-LSTM: a pharmacological representation-based LSTM network for drug-drug interaction extraction.

PeerJ
Pharmacological drug interactions are among the most common causes of medication errors. Many different methods have been proposed to extract drug-drug interactions from the literature to reduce medication errors over the last few years. However, the...

Human motor augmentation with an extra robotic arm without functional interference.

Science robotics
Extra robotic arms (XRAs) are gaining interest in neuroscience and robotics, offering potential tools for daily activities. However, this compelling opportunity poses new challenges for sensorimotor control strategies and human-machine interfaces (HM...

Artificial Intelligence Agents for Materials Sciences.

Journal of chemical information and modeling
The artificial intelligence (AI) tools based on large-language models may serve as a demonstration that we are reaching a groundbreaking new paradigm in which machines themselves will generate knowledge autonomously. This statement is based on the as...

Beyond multilayer perceptrons: Investigating complex topologies in neural networks.

Neural networks : the official journal of the International Neural Network Society
This study delves into the crucial aspect of network topology in artificial neural networks (NNs) and its impact on model performance. Addressing the need to comprehend how network structures influence learning capabilities, the research contrasts tr...