Eric R. Anschuetz

Artificial Intelligence · 2016–2022

A researcher in the Science corpus: 2 papers; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 51 citations into it
• Atomic and Molecular Physics, and Optics — 27 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Scaling & Learning Theory — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it

Whom Eric R. Anschuetz trusts overall

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

1. Diederik P. Kingma
2. Yuanzhi Li
3. Edward Farhi
4. Jarrod R. McClean
5. Harper R. Grimsley
6. Harry Buhrman
7. Jimmy Ba
8. Arthur Pesah
9. Kerstin Beer
10. Yingyu Liang

Papers from Eric R. Anschuetz's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Quantum variational algorithms are swamped with traps (2022) — 318 citations
• Atom-by-atom assembly of defect-free one-dimensional cold atom arrays (2016) — 847 citations