David Wierichs

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it
• Atomic and Molecular Physics, and Optics — 11 citations into it

Whom David Wierichs trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Maria Schuld
2. Edward Farhi
3. Ying Li
4. Nathan Killoran
5. Andrea Mari
6. Kosuke Mitarai
7. James Stokes
8. Atilim Gunes Baydin
9. Josh A. Izaac
10. Simon C. Benjamin

Papers from David Wierichs's perspective

Ordered by how strongly the researchers David Wierichs trusts endorse each paper. Same corpus, a different order for every researcher.

1. A Quantum Approximate Optimization Algorithm
2. Automatic differentiation in PyTorch
3. Quantum circuit learning (Physical Review A)
4. and s
5. Quantum Machine Learning in Feature Hilbert Spaces. (Physical Review Letters)
6. Supervised learning with quantum-enhanced feature spaces (Nature)
7. Classification with Quantum Neural Networks on Near Term Processors
8. Evaluating analytic gradients on quantum hardware (Physical Review A)
9. Quantum autoencoders for efficient compression of quantum data
10. I and J

Their papers

• General parameter-shift rules for quantum gradients (2021) — 388 citations