Michael Moret

Computational Theory and Mathematics · 2018–2023

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

Subfields

• Computational Theory and Mathematics — 54 citations into it
• Artificial Intelligence — 27 citations into it
• Model Architectures — 11 citations into it

Whom Michael Moret trusts overall

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

1. Sepp Hochreiter
2. Nathalie Japkowicz
3. J. Urgen Schmidhuber
4. Ling Li
5. Diederik P. Kingma
6. Marwin H. S. Segler
7. Geoffrey E. Hinton
8. Matthew E. Peters
9. Balaji Lakshminarayanan
10. Yoshua Bengio

Papers from Michael Moret's perspective

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

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

Their papers

• Combining generative artificial intelligence and on-chip synthesis for de novo drug design (2020) — 144 citations
• Leveraging molecular structure and bioactivity with chemical language models for de novo drug design (2023) — 142 citations
• Bidirectional Molecule Generation with Recurrent Neural Networks (2020) — 203 citations
• Automated Gleason grading of prostate cancer tissue microarrays via deep learning (2018) — 425 citations