B. Nebgen

Materials Chemistry · 2018–2019

A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 88 citations into it
• Atomic and Molecular Physics, and Optics — 55 citations into it
• Computational Chemistry & Drug Discovery — 45 citations into it
• Physical and Theoretical Chemistry — 27 citations into it
• AI for Physical Sciences — 22 citations into it
• Artificial Intelligence — 15 citations into it
• Spectroscopy — 15 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom B. Nebgen trusts overall

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

1. Frank Neese
2. Justin S. Smith
3. Sinno Jialin Pan
4. Matthew E. Taylor
5. J. Behler
6. Jeng-Da Chai
7. Qiang Yang
8. M. Head‐Gordon
9. Christoph Riplinger
10. H. Sebastian Seung

Who trusts B. Nebgen overall

1. Justin S. Smith
2. Frank No'e
3. Pascal Friederich
4. Rohit Batra
5. Wenhao Gao

Papers from B. Nebgen's perspective

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

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

Their papers

• Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning (2019) — 591 citations
• Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks. (2018) — 105 citations
• Less is more: sampling chemical space with active learning (2018) — 750 citations
• Outsmarting Quantum Chemistry Through Transfer Learning (2018)