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

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The optimistic gradient method is useful in addressing minimax optimization problems. Motivated by the observation that the conventional stochastic version suffers from the need for a large batch size on the order of O(ϵ-2) to achieve an ϵ-stationary solut ...

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We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particula ...

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

Chattez avec Graph Search

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

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

Efficient and insightful descriptors for representing molecular and material space

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

Thermal conductivity of Li 3 PS 4 solid electrolytes with ab initio accuracy

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Extensions of Peer Prediction Incentive Mechanisms

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

Oxidative Defect Detection Within Free and Packed DNA Systems: A Quantum Mechanical/Molecular Mechanics (QM/ MM) Approach

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

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

Neural Garment Modeling

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

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

Automated all-functionals infrared and Raman spectra

Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning

Diffusion Stochastic Optimization for Min-Max Problems

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

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

Orbital-Resolved DFT plus U for Molecules and Solids