Natalia Dyubankova

Materials Chemistry · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 29 citations into it
• Computational Theory and Mathematics — 27 citations into it
• Computational Chemistry & Drug Discovery — 21 citations into it
• Molecular Biology — 11 citations into it

Whom Natalia Dyubankova trusts overall

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

1. Daniel M. Lowe
2. Marwin H. S. Segler
3. Connor W. Coley
4. Ilya Loshchilov
5. Geoffrey E. Hinton
6. Kaiming He
7. David Weininger
8. Alex Krizhevsky
9. Yoshua Bengio
10. Diederik P. Kingma

Papers from Natalia Dyubankova's perspective

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

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

Their papers

• Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks (2022) — 90 citations
• Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction (2021) — 10 citations