Cover Image

Image Super-resolution Inspired Electron Density Prediction

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Chenghan, Sharir, Or, Yuan, Shunyue, Chan, Garnet K.
Format:	Preprint
Published:	2024
Subjects:	Chemical Physics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Predictive Free Energy Simulations Through Hierarchical Distillation of Quantum Hamiltonians
by: Li, Chenghan, et al.
Published: (2025)

Accurate QM/MM Molecular Dynamics for Periodic Systems in \textsc{GPU4PySCF} with Applications to Enzyme Catalysis
by: Li, Chenghan, et al.
Published: (2024)

General Quantum Alchemical Free Energy Simulations via Hamiltonian Interpolation
by: Li, Chenghan, et al.
Published: (2024)

Ab Initio Many Body Quantum Embedding and Local Correlation in Crystalline Materials using Interpolative Separable Density Fitting
by: Yang, Junjie, et al.
Published: (2026)

Towards Excitations and Dynamical Quantities in Correlated Lattices with Density Matrix Embedding Theory
by: Li, Shuoxue, et al.
Published: (2025)

E3STO: Orbital Inspired SE(3)-Equivariant Molecular Representation for Electron Density Prediction
by: Mitnikov, Ilan, et al.
Published: (2024)

Gaussian Plane-Wave Neural Operator for Electron Density Estimation
by: Kim, Seongsu, et al.
Published: (2024)

Highly Accurate Real-space Electron Densities with Neural Networks
by: Cheng, Lixue, et al.
Published: (2024)

Performant Automatic Differentiation of Local Coupled Cluster Theories: Response Properties and Ab Initio Molecular Dynamics
by: Zhang, Xing, et al.
Published: (2024)

Learning Equivariant Non-Local Electron Density Functionals
by: Gao, Nicholas, et al.
Published: (2024)

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction
by: Zhang, He, et al.
Published: (2024)

Neural Polarization: Toward Electron Density for Molecules by Extending Equivariant Networks
by: Kwak, Bumju, et al.
Published: (2024)

Classical solution of the FeMo-cofactor model to chemical accuracy and its implications
by: Zhai, Huanchen, et al.
Published: (2026)

ELECTRA: A Cartesian Network for 3D Charge Density Prediction with Floating Orbitals
by: Elsborg, Jonas, et al.
Published: (2025)

Orbital Transformers for Predicting Wavefunctions in Time-Dependent Density Functional Theory
by: Zhang, Xuan, et al.
Published: (2026)

Quantum-Inspired Machine Learning for Molecular Docking
by: Shu, Runqiu, et al.
Published: (2024)

Differentiable quantum chemistry with PySCF for molecules and materials at the mean-field level and beyond
by: Zhang, Xing, et al.
Published: (2022)

A Systematic Evaluation of Molecular Mixture Behavior Prediction
by: Leenhouts, Roel J., et al.
Published: (2026)

Surrogate Functionals for Machine-Learned Orbital-Free Density Functional Theory
by: Remme, Roman, et al.
Published: (2026)

Learning Collective Variables with Synthetic Data Augmentation through Physics-Inspired Geodesic Interpolation
by: Yang, Soojung, et al.
Published: (2024)

Quantum chemistry, classical heuristics, and quantum advantage
by: Chan, Garnet Kin-Lic
Published: (2024)

Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning
by: Zhang, He, et al.
Published: (2023)

Interpretable Machine Learning for Quantum-Informed Property Predictions in Artificial Sensing Materials
by: Chen, Li, et al.
Published: (2026)

Quantum Many-Body Linear Algebra, Hamiltonian Moments, and a Coupled Cluster Inspired Framework
by: Ai, Yuhang, et al.
Published: (2025)

Diagonalization without Diagonalization: A Direct Optimization Approach for Solid-State Density Functional Theory
by: Li, Tianbo, et al.
Published: (2024)

Clever Hans in Chemistry: Chemist Style Signals Confound Activity Prediction on Public Benchmarks
by: Blevins, Andrew D., et al.
Published: (2025)

Graph Neural Networks for Surfactant Multi-Property Prediction
by: Brozos, Christoforos, et al.
Published: (2024)

Meta-Learning Linear Models for Molecular Property Prediction
by: Pimonova, Yulia, et al.
Published: (2025)

Self-consistent Validation for Machine Learning Electronic Structure
by: Hu, Gengyuan, et al.
Published: (2024)

DiffBatt: A Diffusion Model for Battery Degradation Prediction and Synthesis
by: Eivazi, Hamidreza, et al.
Published: (2024)

Transfer Learning for Molecular Property Predictions from Small Data Sets
by: Kirschbaum, Thorren, et al.
Published: (2024)

Predicting the Temperature Dependence of Surfactant CMCs Using Graph Neural Networks
by: Brozos, Christoforos, et al.
Published: (2024)

Predicting the Temperature-Dependent CMC of Surfactant Mixtures with Graph Neural Networks
by: Brozos, Christoforos, et al.
Published: (2024)

Coupled-Cluster Imaginary-Time Evolution and the Coupled-Cluster Energy Variance
by: Ai, Yuhang, et al.
Published: (2026)

End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction
by: Lai, Qingsi, et al.
Published: (2024)

Chemically-Informed Machine Learning Approach for Prediction of Reactivity Ratios in Radical Copolymerization
by: Safari, Habibollah, et al.
Published: (2025)

FastCSP: Accelerated Molecular Crystal Structure Prediction with Universal Model for Atoms
by: Gharakhanyan, Vahe, et al.
Published: (2025)

TraceGrad: a Framework Learning Expressive SO(3)-equivariant Non-linear Representations for Electronic-Structure Hamiltonian Prediction
by: Yin, Shi, et al.
Published: (2024)

EDBench: Large-Scale Electron Density Data for Molecular Modeling
by: Xiang, Hongxin, et al.
Published: (2025)

Graph Neural Networks for Temperature-Dependent Activity Coefficient Prediction of Solutes in Ionic Liquids
by: Rittig, Jan G., et al.
Published: (2022)