Rhys E. A. Goodall

Computational Chemistry & Drug Discovery · 2019–2023

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Chemistry & Drug Discovery — 21 citations into it

Whom Rhys E. A. Goodall trusts overall

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

1. George C. Schatz
2. Kaiming He
3. Geoffrey E. Hinton
4. Logan T. Ward

Who trusts Rhys E. A. Goodall overall

1. Amil Merchant
2. Kamal Choudhary
3. Simon L. Batzner
4. Brian L. DeCost

Papers from Rhys E. A. Goodall's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
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. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Predicting materials properties without crystal structure: deep representation learning from stoichiometry (2019) — 346 citations
• A foundation model for atomistic materials chemistry. (2023) — 653 citations
• DeePMD-kit v2: A software package for deep potential models (2023) — 540 citations