Naeimeh Mohseni

Artificial Intelligence · 2022–2023

A researcher in the Science corpus: 2 papers; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 72 citations into it
• Atomic and Molecular Physics, and Optics — 41 citations into it
• Computational Theory and Mathematics — 24 citations into it
• Electrical and Electronic Engineering — 7 citations into it
• Statistical and Nonlinear Physics — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Naeimeh Mohseni trusts overall

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

1. Edward Farhi
2. Andrew Lucas
3. Roman Orus
4. Sanjeev Arora
5. Michel X. Goemans
6. Li Huang
7. Oriol Vinyals
8. Jeffrey Goldstone
9. I. Georgescu
10. Hayato Goto

Who trusts Naeimeh Mohseni overall

1. Peter Leonard McMahon

Papers from Naeimeh Mohseni's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Ising machines as hardware solvers of combinatorial optimization problems (2022) — 614 citations
• Challenges and opportunities in quantum optimization (2023) — 341 citations