Applications of machine learning for studying local solvation environments

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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 ...

Estimating ecosystem-atmosphere fluxes such as evapotranspiration (ET) in a robust manner and at a global scale remains a challenge. Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary ...

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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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Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

This study integrates deep learning and geospatial analysis to enhance soil loss estimation in the Moulouya Watershed, a region prone to erosion due to diverse topography and climatic conditions. Traditional models like the Universal Soil Loss Equation (US ...

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Fiber reinforced polymer confined-recycled aggregate concrete filled steel tube (FRP-RACFST) not only proposes excellent load-bearing capacity and corrosion resistance, but is also an environmentally friendly structure due to the incorporation of recycled ...

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A review is given on the highlights of a scatter-shot approach of developing machine-learning methods and artificial neural networks based fast predictors for the application to fusion exhaust. The aim is to enable and facilitate optimized and improved mod ...

Applications of machine learning for studying local solvation environments

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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

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

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

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

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

Neural Garment Modeling

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

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

Adapting Fine-Grained Cross-View Localization to Areas Without Fine Ground Truth

Stereo Hand-Object Reconstruction for Human-to-Robot Handover

Unsupervised Rhythm and Voice Conversion of Dysarthric to Healthy Speech for ASR

Self-Supervised Anomaly Segmentation via Diffusion Models with Dynamic Transformer UNet

Directly optimizing for synthesizability in generative molecular design using retrosynthesis models

Replica method for computational problems with randomness: principles and illustrations

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Prediction rigidities for data-driven chemistry

Intelligent prediction framework for axial compressive capacity of FRP-RACFST columns

Nissl_3, Raw images for Machine learning for histological annotation and quantification of cortical layers

Eye-Rubbing Detection Using a Smartwatch: A Feasibility Study Demonstrated High Accuracy With Machine Learning

Data-driven models in fusion exhaust: AI methods and perspectives