Tak Hur

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it
• Atomic and Molecular Physics, and Optics — 12 citations into it

Whom Tak Hur trusts overall

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

1. Maria Schuld
2. Yurii E. Nesterov
3. John Preskill
4. Seth Lloyd
5. Ryan Larose
6. Daniel George
7. Ville Bergholm
8. Vittorio Giovannetti
9. Iris Cong
10. Nathan Killoran

Papers from Tak Hur's perspective

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

1. Gradient-based learning applied to document recognition
2. Quantum Machine Learning in Feature Hilbert Spaces. (Physical Review Letters)
3. Evaluating analytic gradients on quantum hardware (Physical Review A)
4. Quantum circuit learning (Physical Review A)
5. Deep Learning
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet classification with deep convolutional neural networks
9. GENERATIVE ADVERSARIAL NETS
10. Hierarchical quantum classifiers (npj Quantum Information)

Their papers

• Quantum convolutional neural network for classical data classification (2021) — 385 citations