Plasma confinement mode classification using a sequence-to-sequence neural network with attention

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Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to catheteri ...

The capabilities of deep learning systems have advanced much faster than our ability to understand them. Whilst the gains from deep neural networks (DNNs) are significant, they are accompanied by a growing risk and gravity of a bad outcome. This is troubli ...

This paper introduces a novel architecture for Quantum Graph Neural Networks, which is significantly different from previous approaches found in the literature. The proposed approach produces similar outcomes with respect to previous models but with fewer ...

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Plasma confinement mode classification using a sequence-to-sequence neural network with attention

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Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

Safe Deep Neural Networks

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Harnessing deep learning to detect bronchiolitis obliterans syndrome from chest CT

Global fluid simulations of plasma turbulence in stellarators

t-PiNet: A thermodynamics-informed hierarchical learning for discovering constitutive relations of geomaterials

Nonlinear simulation of plasma turbulence using a gyrokinetic moment-based approach

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

Random matrix methods for high-dimensional machine learning models

Machine Learning Applications to Conditional Asset Pricing: Attention, CNNs, and Neural Tangent Kernels

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

MetaCap: Meta-learning Priors from Multi-view Imagery for Sparse-View Human Performance Capture and Rendering

Long plasma duration operation analyses with an international multi-machine (tokamaks and stellarators) database

Enhancing skin lesion classification: a CNN approach with human baseline comparison

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

On the added value of sequential deep learning for the upscaling of evapotranspiration

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

Towards practical reinforcement learning for tokamak magnetic control