Picture for Peter Zaspel

Peter Zaspel

Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials

Add code
Oct 27, 2024
Viaarxiv icon

Benchmarking Data Efficiency in $Δ$-ML and Multifidelity Models for Quantum Chemistry

Add code
Oct 15, 2024
Viaarxiv icon

Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies

Add code
Oct 15, 2024
Figure 1 for Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
Figure 2 for Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
Figure 3 for Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
Figure 4 for Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
Viaarxiv icon

Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties

Add code
Jul 24, 2024
Viaarxiv icon

Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes

Add code
Jun 26, 2024
Viaarxiv icon

CheMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules

Add code
Jun 20, 2024
Figure 1 for CheMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
Figure 2 for CheMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
Figure 3 for CheMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
Figure 4 for CheMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
Viaarxiv icon

Multi-Fidelity Machine Learning for Excited State Energies of Molecules

Add code
May 18, 2023
Viaarxiv icon

Towards data-driven filters in Paraview

Add code
Aug 12, 2021
Figure 1 for Towards data-driven filters in Paraview
Figure 2 for Towards data-driven filters in Paraview
Figure 3 for Towards data-driven filters in Paraview
Figure 4 for Towards data-driven filters in Paraview
Viaarxiv icon