AIMC Topic: Learning

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Fast protein structure comparison through effective representation learning with contrastive graph neural networks.

PLoS computational biology Mar 24, 2022
Protein structure alignment algorithms are often time-consuming, resulting in challenges for large-scale protein structure similarity-based retrieval. There is an urgent need for more efficient structure comparison approaches as the number of protein...
Neural Networks, Computer Software Algorithms Learning Proteins
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CircuitBot: Learning to survive with robotic circuit drawing.

PloS one Mar 24, 2022
Robots with the ability to actively acquire power from surroundings will be greatly beneficial for long-term autonomy and to survive in uncertain environments. In this work, a scenario is presented where a robot has limited energy, and the only way t...
Learning Robotics Bayes Theorem Robotic Surgical Procedures
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Exploration in neo-Hebbian reinforcement learning: Computational approaches to the exploration-exploitation balance with bio-inspired neural networks.

Neural networks : the official journal of the International Neural Network Society Mar 23, 2022
Recent theoretical and experimental works have connected Hebbian plasticity with the reinforcement learning (RL) paradigm, producing a class of trial-and-error learning in artificial neural networks known as neo-Hebbian plasticity. Inspired by the ro...
Neural Networks, Computer Learning Reward Reinforcement, Psychology
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Instance importance-Aware graph convolutional network for 3D medical diagnosis.

Medical image analysis Mar 18, 2022
Automatic diagnosis of 3D medical data is a significant goal of intelligent healthcare. By exploiting the abundant pathological information of 3D data, human experts and algorithms can provide accurate predictions for patients. Considering the high c...
Humans Neural Networks, Computer Algorithms Learning
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Bimanual motor skill learning with robotics in chronic stroke: comparison between minimally impaired and moderately impaired patients, and healthy individuals.

Journal of neuroengineering and rehabilitation Mar 17, 2022
BACKGROUND: Most activities of daily life (ADL) require cooperative bimanual movements. A unilateral stroke may severely impair bimanual ADL. How patients with stroke (re)learn to coordinate their upper limbs (ULs) is largely unknown. The objectives ...
Humans Learning Robotics Stroke Motor Skills Stroke Rehabilitation
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Signed random walk diffusion for effective representation learning in signed graphs.

PloS one Mar 17, 2022
How can we model node representations to accurately infer the signs of missing edges in a signed social graph? Signed social graphs have attracted considerable attention to model trust relationships between people. Various representation learning met...
Humans Neural Networks, Computer Learning Diffusion
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Learning a discriminative SPD manifold neural network for image set classification.

Neural networks : the official journal of the International Neural Network Society Mar 16, 2022
Performing pattern analysis over the symmetric positive definite (SPD) manifold requires specific mathematical computations, characterizing the non-Euclidian property of the involved data points and learning tasks, such as the image set classificatio...
Neural Networks, Computer Machine Learning Algorithms Learning
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Motor-related signals support localization invariance for stable visual perception.

PLoS computational biology Mar 14, 2022
Our ability to perceive a stable visual world in the presence of continuous movements of the body, head, and eyes has puzzled researchers in the neuroscience field for a long time. We reformulated this problem in the context of hierarchical convoluti...
Neural Networks, Computer Learning Animals Mammals Vision, Ocular Visual Perception
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Optimal Control of Whole Network Control System Using Improved Genetic Algorithm and Information Integrity Scale.

Computational intelligence and neuroscience Mar 14, 2022
WNCS (Whole network control system) is a network-based distributed control system. The control loop formed by the serial network usually includes several subcontrol systems. WNCS optimal control is a complex and multiparameter coupled highly nonlinea...
Neural Networks, Computer Algorithms Computer Simulation Learning Computer Communication Networks
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Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification.

Medical image analysis Mar 12, 2022
Morphological abnormalities of the femoroacetabular (hip) joint are among the most common human musculoskeletal disorders and often develop asymptomatically at early easily treatable stages. In this paper, we propose an automated framework for landma...
Humans Neural Networks, Computer Learning Magnetic Resonance Imaging Hip Joint
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