Cover Image

Optimized Multifidelity Machine Learning for Quantum Chemistry

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Vinod, Vivin, Kleinekathöfer, Ulrich, Zaspel, Peter
Format:	Preprint
Published:	2023
Subjects:	Chemical Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Benchmarking Data Efficiency in $Δ$-ML and Multifidelity Models for Quantum Chemistry
by: Vinod, Vivin, et al.
Published: (2024)

Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties
by: Vinod, Vivin, et al.
Published: (2024)

Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
by: Vinod, Vivin, et al.
Published: (2024)

QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
by: Vinod, Vivin, et al.
Published: (2024)

Multi-Fidelity Machine Learning for Excited State Energies of Molecules
by: Vinod, Vivin, et al.
Published: (2023)

Excitation Energy Transfer between Porphyrin Dyes on a Clay Surface: A study employing Multifidelity Machine Learning
by: Lyu, Dongyu, et al.
Published: (2024)

LFaB: Low fidelity as Bias for Active Learning in the chemical configuration space
by: Vinod, Vivin, et al.
Published: (2025)

Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials
by: Holzenkamp, Matthias, et al.
Published: (2024)

Excitation Energy Transfer between Porphyrin Dyes on a Clay Surface: A Study Employing Multifidelity Machine Learning
by: Dongyu Lyu, et al.
Published: (2025)

Spectral Densities, Structured Noise and Ensemble Averaging within Open Quantum Dynamics
by: Holtkamp, Yannick Marcel, et al.
Published: (2024)

Predicting Molecular Energies of Small Organic Molecules With Multi‐Fidelity Methods
by: Vivin Vinod, et al.
Published: (2025)

Excitation of Low-Frequency Modes and the Effects of Protein Dynamics on Spectral Densities of Bacteriochlorophyll Molecules
by: Maity, Sayan, et al.
Published: (2026)

Open Source Variational Quantum Eigensolver Extension of the Quantum Learning Machine (QLM) for Quantum Chemistry
by: Haidar, Mohammad, et al.
Published: (2022)

Construction of Chemistry Inspired Dynamic Ansatz Utilizing Generative Machine Learning
by: Halder, Sonaldeep, et al.
Published: (2025)

A Machine Learning Model for the Chemistry of a Solvated Electron
by: Gao, Ruiqi, et al.
Published: (2025)

Variational Quantum Annealing for Quantum Chemistry
by: Yip, Ka-Wa, et al.
Published: (2025)

Quantum Chemistry Driven Molecular Inverse Design with Data-free Reinforcement Learning
by: Calcagno, Francesco, et al.
Published: (2025)

Towards Quantum Advantage in Chemistry
by: Genin, Scott N., et al.
Published: (2025)

Condensed-Phase Quantum Chemistry
by: Robinson, Paul J., et al.
Published: (2024)

Machine Learning for Polaritonic Chemistry: Accessing chemical kinetics
by: Schäfer, Christian, et al.
Published: (2023)

Reactive Chemistry at Unrestricted Coupled Cluster Level: High-throughput Calculations for Training Machine Learning Potentials
by: Allen, Alice E. A., et al.
Published: (2025)

Quantum Solvers for Nonlinear Matrix Equations in Quantum Chemistry
by: Rodenas-Ruiz, Pablo, et al.
Published: (2026)

Foundations of Quantum Information for Physical Chemistry
by: Wu, Weijun, et al.
Published: (2023)

Reducing Numerical Precision Requirements in Quantum Chemistry Calculations
by: Dawson, William, et al.
Published: (2024)

QDK/Chemistry: A Modular Toolkit for Quantum Chemistry Applications
by: Baker, Nathan A., et al.
Published: (2026)

An Introduction to Variational Quantum Eigensolver Applied to Chemistry
by: Fonseca, Matheus da S., et al.
Published: (2025)

Size-Consistent Quantum Chemistry on Quantum Computers
by: Garrett, Noah, et al.
Published: (2025)

Forte: A Suite of Advanced Multireference Quantum Chemistry Methods
by: Evangelista, Francesco A., et al.
Published: (2024)

A Deterministic Framework for Neural Network Quantum States in Quantum Chemistry
by: Che, Zheng
Published: (2026)

Algebraic Varieties in Quantum Chemistry
by: Faulstich, Fabian, et al.
Published: (2023)

High Performance Quantum Emulation for Chemistry Applications with Hyperion
by: Adjoua, Olivier, et al.
Published: (2026)

Quantum Machine Learning of Molecular Energies with Hybrid Quantum-Neural Wavefunction
by: Li, Weitang, et al.
Published: (2025)

Automated Quantum Chemistry Code Generation with the p$^\dagger$q Package
by: Liebenthal, Marcus D., et al.
Published: (2025)

Leveraging Machine Learning to Overcome Limitations in Quantum Algorithms
by: Sala, Laia Coronas, et al.
Published: (2024)

Fault-tolerant Quantum Chemical Calculations with Improved Machine-Learning Models
by: Yuan, Kai, et al.
Published: (2024)

Molecular Quantum Chemical Data Sets and Databases for Machine Learning Potentials
by: Ullah, Arif, et al.
Published: (2024)

State-Averaged Quantum Algorithms for Multiconfigurational Surface Chemistry: A Benchmark on Rh@TiO2(110)
by: Larsson, Ernst Dennis Lægteskov Binau, et al.
Published: (2026)

Shallow Electronic State Preparation for Quantum Chemistry with Quantum Monte Carlo Pre-Selection
by: Welling, Eline, et al.
Published: (2026)

Excited-State Quantum Chemistry on Qumode-Based Processors via Variational Quantum Deflation
by: Jost, Marlon F., et al.
Published: (2026)

Symmetry Dilemmas in Quantum Computing for Chemistry: A Comprehensive Analysis
by: Magoulas, Ilias, et al.
Published: (2025)