Nina Mazyavkina

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Reinforcement Learning — 17 citations into it
• Graph Learning — 8 citations into it
• Computational Theory and Mathematics — 5 citations into it

Whom Nina Mazyavkina trusts overall

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

1. Ronald J. Williams
2. Richard S. Sutton
3. Richard Bellman
4. Oriol Vinyals
5. David Haussler
6. Yoshua Bengio
7. Geoffrey E. Hinton
8. Diederik P. Kingma
9. Volodymyr Mnih
10. Alex Krizhevsky

Papers from Nina Mazyavkina's perspective

Ordered by how strongly the researchers Nina Mazyavkina 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Reinforcement Learning for Combinatorial Optimization: A Survey (2020) — 800 citations