Peter Zaspel

21 papers Journal 19Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials.
Mach. Learn. Sci. Technol.
Matthias Holzenkamp, Dongyu Lyu, Ulrich Kleinekathöfer, Peter Zaspel
2025 J jnl
LoUQAL: Low-fidelity informed Uncertainty Quantification for Active Learning in the chemical configuration space.
CoRR
Vivin Vinod, Peter Zaspel
2024 J jnl
Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties.
CoRR
Vivin Vinod, Peter Zaspel
2024 J jnl
Assessing non-nested configurations of multifidelity machine learning for quantum-chemical properties.
Mach. Learn. Sci. Technol.
Vivin Vinod, Peter Zaspel
2024 J jnl
Benchmarking Data Efficiency in Δ-ML and Multifidelity Models for Quantum Chemistry.
CoRR
Vivin Vinod, Peter Zaspel
2024 J jnl
CheMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules.
CoRR
Vivin Vinod, Peter Zaspel
2024 J jnl
Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes.
CoRR
Peter Zaspel, Michael Günther
2024 J jnl
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials.
CoRR
Matthias Holzenkamp, Dongyu Lyu, Ulrich Kleinekathöfer, Peter Zaspel
2024 J jnl
Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies.
CoRR
Vivin Vinod, Peter Zaspel
2024 J jnl
Optimized multifidelity machine learning for quantum chemistry.
Mach. Learn. Sci. Technol.
Vivin Vinod, Ulrich Kleinekathöfer, Peter Zaspel
2023 J jnl
Multi-Fidelity Machine Learning for Excited State Energies of Molecules.
CoRR
Vivin Vinod, Sayan Maity, Peter Zaspel, Ulrich Kleinekathöfer
2021 J jnl
Towards data-driven filters in Paraview.
CoRR
Drishti Maharjan, Peter Zaspel
2019 J jnl
Algorithmic Patterns for $$\mathcal {H}$$ H -Matrices on Many-Core Processors.
J. Sci. Comput.
Peter Zaspel
2019 J jnl
On the Algebraic Construction of Sparse Multilevel Approximations of Elliptic Tensor Product Problems.
J. Sci. Comput.
Helmut Harbrecht, Peter Zaspel
2018 J jnl
A scalable H-matrix approach for the solution of boundary integral equations on multi-GPU clusters.
CoRR
Helmut Harbrecht, Peter Zaspel
2017 J jnl
Algorithmic patterns for H-matrices on many-core processors.
CoRR
Peter Zaspel
2016 J jnl
Uncertainty Quantification and High Performance Computing (Dagstuhl Seminar 16372).
Dagstuhl Reports
Vincent Heuveline, Michael Schick, Clayton G. Webster, Peter Zaspel
2014 — conf
EXAHD: An Exa-scalable Two-Level Sparse Grid Approach for Higher-Dimensional Problems in Plasma Physics and Beyond.
Euro-Par Workshops (2)
Dirk Pflüger, Hans-Joachim Bungartz, Michael Griebel, Frank Jenko, Tilman Dannert, Mario Heene, Christoph Kowitz, Alfredo Parra-Hinojosa, Peter Zaspel
2011 — conf
Massively Parallel Fluid Simulations on Amazon's HPC Cloud.
NCCA
Peter Zaspel, Michael Griebel
2011 J jnl
Photorealistic visualization and fluid animation: coupling of Maya with a two-phase Navier-Stokes fluid solver.
Comput. Vis. Sci.
Peter Zaspel, Michael Griebel
2010 J jnl
A multi-GPU accelerated solver for the three-dimensional two-phase incompressible Navier-Stokes equations.
Comput. Sci. Res. Dev.
Michael Griebel, Peter Zaspel