Daniel Veltri

Molecular Biology · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Molecular Biology — 22 citations into it; #12,975 of 17,773 by trust here, #16,150 by citations
• Artificial Intelligence — 14 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• Model Architectures — 6 citations into it

Whom Daniel Veltri trusts overall

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

1. Geoffrey E. Hinton
2. Kuo-Chen Chou
3. W. James Kent
4. J. Urgen Schmidhuber
5. Sepp Hochreiter
6. Yoshua Bengio
7. Dzmitry Bahdanau
8. L. V. D. van der Maaten
9. Alex Krizhevsky
10. Diederik P. Kingma

Who trusts Daniel Veltri overall

1. John Muschelli
2. Payel Das

Papers from Daniel Veltri's perspective

Ordered by how strongly the researchers Daniel Veltri 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Deep learning improves antimicrobial peptide recognition (2018) — 497 citations
• Structure and function of a malaria transmission blocking vaccine targeting Pfs230 and Pfs230-Pfs48/45 proteins (2020) — 51 citations