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RESEARCH PAPER · Journal of Chemical Theory and Computation · 2019

Regression Clustering for Improved Accuracy and Training Costs with Molecular-Orbital-Based Machine Learning

Lixue Cheng, Nikola Kovachki, Matthew Welborn, Thomas F. Miller

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42 direct citing works

Regression Clustering for Improved Accuracy and Training Costs with Molecular-Orbital-Based Machine LearningOriginalPhysical machine learning outperforms "human learning" in Quantum Chemistry3Ground State Energy Functional with Hartree–Fock Efficiency and Chemical Accuracy72OrbNet: Deep learning for quantum chemistry using symmetry-adapted atomic-orbital features242Transferable MP2-Based Machine Learning for Accurate Coupled-Cluster Energies33Machine-learned electron correlation model based on frozen core approximation16Mean-field density matrix decompositions14DeePKS: A Comprehensive Data-Driven Approach toward Chemically Accurate Density Functional Theory87Quantum Information and Algorithms for Correlated Quantum Matter125The Analysis of Internet Commercial Judicial Based on Big Data Alliance and Mining Service Process Model4A Machine Learning Approach for MP2 Correlation Energies and Its Application to Organic Compounds20Pure non-local machine-learned density functional theory for electron correlation74A clustering based Swarm Intelligence optimization technique for the Internet of Medical Things53Improved accuracy and transferability of molecular-orbital-based machine learning: Organics, transition-metal complexes, non-covalent interactions, and transition states51Machine Learning Solvation Environments in Conductive Polymers: Application to ProDOT-2Hex with Solvent Swelling14Analytical gradients for molecular-orbital-based machine learning13Clinical Influencing Factors of Acute Myocardial Infarction Based on Improved Machine Learning13Fast Estimation of Møller–Plesset Correlation Energies Based on Atomic Contributions9RETRACTED ARTICLE: The Cultivation of Innovation and Entrepreneurship Skills and Teaching Strategies for College Students from the Perspective of Big Data4Machine learning and materials informatics approaches for evaluating the interfacial properties of fiber-reinforced composites69Model Reduction And Neural Networks For Parametric PDEs329Machine-Learned Energy Functionals for Multiconfigurational Wave Functions24Clue mining based on the online gambling intelligent robot customer service platform2RETRACTED ARTICLE: Research on the therapeutic effects of drugs for patients with mental illness based on cluster analysis0Unsupervised View-Selective Deep Learning for Practical Indoor Localization Using CSI22Application of digital intelligent communication technology in contemporary comparative education methodology13Quantum Deep Descriptor: Physically Informed Transfer Learning from Small Molecules to Polymers25Recursive Hierarchical Regression Clustering0Molecular representations for machine learning applications in chemistry93Application of Intelligent Sensor Algorithm in Student Management Information Fusion15Designing a multilayer film via machine learning of scientific literature8An orbital-based representation for accurate quantum machine learning19Accurate, affordable, and generalizable machine learning simulations of transition metal x-ray absorption spectra using the XANESNET deep neural network43Review on the lithium transport mechanism in solid‐state battery materials58Fast Near Ab Initio Potential Energy Surfaces Using Machine Learning25Scalable computer interactive education system based on large-scale multimedia data analysis2Recent progress in generative adversarial networks applied to inversely designing inorganic materials: A brief review50Computational Technologies for IoT Networks Application in English Classroom Teaching3Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space18Molecular dipole moment learning via rotationally equivariant derivative kernels in molecular-orbital-based machine learning7Molecular-orbital-based machine learning for open-shell and multi-reference systems with kernel addition Gaussian process regression12A Comparative Study of Regression Machine Learning Algorithms: Tradeoff Between Accuracy and Computational Complexity32Machine Learning Quantum Mechanics Computer Simulations0Risk assessment of computer network information using a proposed approach: Fuzzy hierarchical reasoning model based on scientific inversion parallel programming1Data-Driven Refinement of Electronic Energies from Two-Electron Reduced-Density-Matrix Theory13Machine learning-guided REIMS pattern recognition of non-dairy cream, milk fat cream and whipping cream for fraudulence identification19Low-Data Deep Quantum Chemical Learning for Accurate MP2 and Coupled-Cluster Correlations12Machine-learned constitutive relations for mechanoluminescent ZnS:Cu–PDMS composites2Orbital-Free Density Functional Theory: An Attractive Electronic Structure Method for Large-Scale First-Principles Simulations115Divide-and-conquer potentials enable scalable and accurate predictions of forces and energies in atomistic systems6Making quantum chemistry compressive and expressive: Toward practical ab‐initio simulation4Efficient clustering of large molecular libraries8Assessing zero-shot generalisation behaviour in graph-neural-network interatomic potentials1BitBIRCH: efficient clustering of large molecular libraries23Accurate Neural Network Fine-Tuning Approach for Transferable Ab Initio Energy Prediction across Varying Molecular and Crystalline Scales8Machine Learning Approaches for Developing Potential Surfaces: Applications to OH – (H 2 O) n ( n = 1–3) Complexes5Transferability Across Different Molecular Systems and Levels of Theory with the Data-Driven Coupled-Cluster Scheme5Multiproperty Deep Learning of the Correlation Energy of Electrons and the Physicochemical Properties of Molecules5A Deep Learning-Augmented Density Functional Framework for Reaction Modeling with Chemical Accuracy6Extension of Composite Method and Machine‐Learned Electron Correlation Model to Fourth‐Period Elements0Predicting the Post-Hartree-Fock Electron Correlation Energy of Complex Systems with the Information-Theoretic Approach3Diffusion Monte Carlo Study of the Structure and Spectroscopy of H 3 O –0Can the FCI energies/properties be predicted with HF/DFT densities?3Computation-assisted probing of the solid-solid interface in all-solid-state sodium-ion batteries1LiClustCondAI: A clustering-based ensemble regression framework for ionic conductivity predictions in solid-state electrolytes0Integrating Coupled‐Cluster Theory Within AI Workflows for Accurate Molecular Geometries0

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