Mikhail Salnikov

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 34 citations into it
• Computer Vision and Pattern Recognition — 13 citations into it
• Model Architectures — 12 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Neural Architecture Search & AutoML — 7 citations into it
• Optimization & Training — 7 citations into it

Whom Mikhail Salnikov trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Kaiming He
4. Ilya Sutskever
5. Tomas Mikolov
6. Alex Krizhevsky
7. Sepp Hochreiter
8. Quoc V. Le
9. Diederik P. Kingma
10. Frank Hutter

Papers from Mikhail Salnikov's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
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

• NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing (2020) — 135 citations