Davide Sabbadin

Computational Theory and Mathematics · 2019

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 22 citations into it
• Molecular Biology — 19 citations into it
• Materials Chemistry — 18 citations into it
• Computational Chemistry & Drug Discovery — 14 citations into it

Whom Davide Sabbadin trusts overall

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

1. Marwin H. S. Segler
2. Sepp Hochreiter
3. Teague Sterling

Papers from Davide Sabbadin's perspective

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

1. Long Short-Term Memory
2. Molecular de-novo design through deep reinforcement learning
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Neural-Symbolic Machine Learning for Retrosynthesis and Reaction Prediction.
7. Gradient-based learning applied to document recognition
8. Protein-Ligand Scoring with Convolutional Neural Networks
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Shape-Based Generative Modeling for de Novo Drug Design (2019) — 208 citations