Stephanie Wills

Computational Chemistry & Drug Discovery · 2022–2023

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Chemistry & Drug Discovery — 10 citations into it

Whom Stephanie Wills trusts overall

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

1. L. V. D. van der Maaten
2. Darko Butina
3. Geoffrey E. Hinton
4. Anna Gaulton

Papers from Stephanie Wills's perspective

Ordered by how strongly the researchers Stephanie Wills 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet Large Scale Visual Recognition Challenge
9. Going deeper with convolutions
10. Visualizing Data using t-SNE

Their papers

• Fragment Merging Using a Graph Database Samples Different Catalogue Space than Similarity Search (2023) — 21 citations
• The use of a graph database is a complementary approach to a classical similarity search for identifying commercially available fragment merges (2022)