AIMC Topic: Learning

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Toward biologically plausible artificial vision.

The Behavioral and brain sciences
Quilty-Dunn et al. argue that deep convolutional neural networks (DCNNs) optimized for image classification exemplify structural disanalogies to human vision. A different kind of artificial vision - found in reinforcement-learning agents navigating a...

Neuromorphic sequence learning with an event camera on routes through vegetation.

Science robotics
For many robotics applications, it is desirable to have relatively low-power and efficient onboard solutions. We took inspiration from insects, such as ants, that are capable of learning and following routes in complex natural environments using rela...

Walking and falling: Using robot simulations to model the role of errors in infant walking.

Developmental science
What is the optimal penalty for errors in infant skill learning? Behavioral analyses indicate that errors are frequent but trivial as infants acquire foundational skills. In learning to walk, for example, falling is commonplace but appears to incur o...

On the visual analytic intelligence of neural networks.

Nature communications
Visual oddity task was conceived to study universal ethnic-independent analytic intelligence of humans from a perspective of comprehension of spatial concepts. Advancements in artificial intelligence led to important breakthroughs, yet excelling at s...

How to backdoor split learning.

Neural networks : the official journal of the International Neural Network Society
Split learning, a distributed learning framework, has garnered significant attention from academic and industrial communities. In contrast to federated learning, split learning offers a more flexible architecture for participants with limited computi...

Does GPT-4 have neurophobia? Localization and diagnostic accuracy of an artificial intelligence-powered chatbot in clinical vignettes.

Journal of the neurological sciences
BACKGROUND AND OBJECTIVES: This is an observational study of the performance of an artificial intelligence-powered chatbot tasked with solving unknown neurologic case vignettes. The primary objective of the study is to assess the current capabilities...

FOESO-Net: A specific neural network for fast sensorless robot manipulator torque estimation.

Neural networks : the official journal of the International Neural Network Society
Contact torque sensing allows robot manipulators to cooperate with humans and detect accidental collisions in real time to ensure safety. Most sensorless torque estimation schemes, which are based on linear observer approaches, cannot compromise betw...

Signatures of task learning in neural representations.

Current opinion in neurobiology
While neural plasticity has long been studied as the basis of learning, the growth of large-scale neural recording techniques provides a unique opportunity to study how learning-induced activity changes are coordinated across neurons within the same ...

Joint learning of feature and topology for multi-view graph convolutional network.

Neural networks : the official journal of the International Neural Network Society
Graph convolutional network has been extensively employed in semi-supervised classification tasks. Although some studies have attempted to leverage graph convolutional networks to explore multi-view data, they mostly consider the fusion of feature an...

AI pitfalls and what not to do: mitigating bias in AI.

The British journal of radiology
Various forms of artificial intelligence (AI) applications are being deployed and used in many healthcare systems. As the use of these applications increases, we are learning the failures of these models and how they can perpetuate bias. With these n...