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Frederik Wilde
Observed names:
F Wilde,
Wilde, Frederik
Institution:
Freie Universität Berlin
Observed institution:
Freie Universität Berlin
ORCID:
0000-0002-6224-1964
Observed ORCID:
0000-0002-6224-1964
OpenAlex ID:
A5085237366
Stochastic gradient descent for hybrid quantum-classical optimization
2020
·
Ryan Sweke
, Frederik Wilde
, et al.
·
Quantum
·
219
An in-principle super-polynomial quantum advantage for approximating combinatorial optimization problems via computational learning theory
2024
·
Niklas Pirnay
, Vincent Ulitzsch
, et al.
·
Science Advances
·
27
PDF
Stochastic noise can be helpful for variational quantum algorithms
2025
·
Junyu Liu
, Frederik Wilde
, et al.
·
Physical Review A
·
21
PDF
Scalably learning one-dimensional quantum many-body Hamiltonians from dynamical data
2026
·
F Wilde
, A Kshetrimayum
, et al.
·
Quantum Science and Technology
·
13
Stochastic noise can be helpful for variational quantum algorithms
2022
·
Liu, Junyu
, Wilde, Frederik
, et al.
·
arXiv (Cornell University)
·
13
PDF
Single-component gradient rules for variational quantum algorithms
2022
·
Thomas Hubregtsen
, Frederik Wilde
, et al.
·
Quantum Science and Technology
·
11
PDF
Stochastic Gradient Descent for Hybrid Quantum-Classical Optimization
2020
·
Frederik Wilde
, Ryan Sweke
, et al.
·
Bulletin of the American Physical Society
·
8
Learning Topological States from Randomized Measurements Using Variational Tensor-Network Tomography
2025
·
Yanting Teng
, Rhine Samajdar
, et al.
·
PRX Quantum
·
6
An in-principle super-polynomial quantum advantage for approximating combinatorial optimization problems via computational learning theory
2022
·
Pirnay, Niklas
, Ulitzsch, Vincent
, et al.
·
arXiv (Cornell University)
·
3
PDF
variPEPS (Python version)
2024
·
Naumann, Jan
, Schmoll, Philipp
, et al.
·
Zenodo (CERN European Organization for Nuclear Research)
·
1
variPEPS (Python version)
2024
·
Naumann, Jan
, Schmoll, Philipp
, et al.
·
Zenodo (CERN European Organization for Nuclear Research)
·
1
Scalably learning quantum many-body Hamiltonians from dynamical data
2022
·
Wilde, Frederik
, Kshetrimayum, Augustine
, et al.
·
Zenodo (CERN European Organization for Nuclear Research)
·
1
Scalably learning one-dimensional quantum many-body Hamiltonians from dynamical data
2026
·
Wilde, Frederik
, Kshetrimayum, Augustine
, et al.
·
Fraunhofer-Publica (Fraunhofer-Gesellschaft)
variPEPS (Python version)
2025
·
Naumann, Jan
, Schmoll, Philipp
, et al.
·
Zenodo (CERN European Organization for Nuclear Research)
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Works count:
15
Citation count:
324
H-index:
7
I10-index:
6
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