A. Pais

Materials Chemistry · with Cova · 2019

A researcher in the Science corpus: 1 paper; trusts 47 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 60 citations into it
• Computational Theory and Mathematics — 51 citations into it
• Computational Chemistry & Drug Discovery — 28 citations into it
• Molecular Biology — 23 citations into it
• Atomic and Molecular Physics, and Optics — 13 citations into it
• AI for Physical Sciences — 10 citations into it
• Physical and Theoretical Chemistry — 10 citations into it
• Environmental Chemistry — 6 citations into it

Whom A. Pais trusts overall

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

1. Matthias Rupp 
2. J. Behler
3. Marwin H. S. Segler
4. Jure Zupan
5. John B. O. Mitchell
6. Suman K. Chakravarti
7. Katja Hansen
8. R. Ramakrishnan
9. V. Botu
10. Adam C. Mater

Papers from A. Pais's perspective

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

1. Gradient-based learning applied to document recognition
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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet Large Scale Visual Recognition Challenge
9. Going deeper with convolutions
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns (2019) — 151 citations