Investigation of the role of spinal circuits in human motor control, from healthy to rehabilitation conditions

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We investigate reduced order models for acoustic and electromagnetic wave problems in parametrically defined domains. The parameter-to-solution maps are approximated following the so-called Galerkin POD-NN method, which combines the construction of a reduc ...

Reservoir Computing (RC) has become popular in recent years thanks to its fast and efficient computational capabilities. Standard RC has been shown to be equivalent in the asymptotic limit to Recurrent Kernels, which helps in analyzing its expressive power ...

Hyperbolic conservation laws play a critical role in various fields, including aerodynamics, physics, and oceanography. However, traditional physics-informed neural networks (PINNs), despite their remarkable capabilities in solving partial differential equ ...

Rock cuttings from destructive boreholes are a common and cheaper source of drilling materials that can be used to determine underground geology compared to rock core samples. Classifying manually the series of cuttings can be a long and tedious process an ...

Wearable Sensor (WS)-based monitoring systems detect minute patient movements/ demands and abnormalities through periodic sensing and imaging. Sensor data observed over different intervals is not constant or available based on operating sequences. Due to v ...

Precisely localizing anomalies in medical images remains a significant challenge due to their heterogeneous nature across modalities and organs. While initial efforts excelled in identifying prominent anomalies, detecting minute target lesions posed signif ...

Forearm pronosupination is an essential movement for many activities of daily living as it complements hand manipulation. Despite being highly impaired in individuals with spinal cord injury (SCI), it is rarely assisted by wearable robots, likely due to th ...

A computer-implemented method of training a neural network for generating upper or lower limb motion control signals to operate a virtual, robotic or prosthetic upper or lower limb, comprising providing or receiving, at a neural network, electromyographic ...

Lower urinary tract dysfunction, such as incontinence or urinary retention, is one of the leading consequences of neurological diseases. This significantly impacts the quality of life for those affected, with implications extending not only to humans but a ...

Regression models often fail to generalize effectively in regions characterized by highly imbalanced label distributions. Previous methods for deep imbalanced regression rely on gradient-based weight updates, which tend to overfit in underrepresented regio ...

Here we provide the weights of the neural network policies used for the analysis presented in our article. The archives whose names start with a number (01 - 32) correspond to the 32 curriculum steps to train the Baoding Balls policy which ranked first at ...

Planning and execution of voluntary movement depend on the contribution of distinct classes of neurons in primary motor and premotor areas. However, timing and pattern of activation of GABAergic cells during specific motor behaviors remain only partly unde ...

Years of a fierce competition have naturally selected the fittest deep learning algorithms. Yet, although these models work well in practice, we still lack a proper characterization of why they do so. This poses serious questions about the robustness, trus ...

This paper provides a theoretical study of deep neural function approximation in reinforcement learning (RL) with the ϵ-greedy exploration under the online setting. This problem setting is motivated by the successful deep Q-networks (DQN) framework that fa ...

The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of finite-temperature fluctuations. To reach this goal, a diverse set of methods has been pr ...

A major goal shared by neuroscience and collective behavior is to understand how dynamic interactions between individual elements give rise to behaviors in populations of neurons and animals, respectively. This goal has recently become within reach, thanks ...

Investigation of the role of spinal circuits in human motor control, from healthy to rehabilitation conditions

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Galerkin neural network-POD for acoustic and electromagnetic wave propagation in parametric domains

Comparison of Reservoir Computing topologies using the Recurrent Kernel approach

A coordinate transformation-based physics-informed neural networks for hyperbolic conservation laws

X-ray Micro-CT based characterization of rock cuttings with deep learning

Enhancing wearable sensor data analysis for patient health monitoring using allied data disparity technique and multi instance ensemble perceptron learning

Robust semantic learning for precise medical image segmentation

A Soft Pneumatic Exosuit to Assist Pronosupination in Individuals with Spinal Cord Injury

Wearable electromyographic device and system and methods for motion decoding of body parts

Swine Pudendal Nerve as a Model for Neuromodulation Studies to Restore Lower Urinary Tract Dysfunction

IM-Context: In-Context Learning for Imbalanced Regression Tasks

Acquiring musculoskeletal skills with curriculum-based reinforcement learning - model weights

Fast-Spiking Interneurons of the Premotor Cortex Contribute to Initiation and Execution of Spontaneous Actions

The inductive bias of deep learning: Connecting weights and functions

Understanding Deep Neural Function Approximation in Reinforcement Learning via ϵ-Greedy Exploration

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

Connecting the dots in ethology: applying network theory to understand neural and animal collectives