David Samuel

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it; #28,761 of 35,345 by trust here, #34,213 by citations
• Signal Processing — 11 citations into it; #6,100 of 7,572 by trust here, #7,324 by citations
• Computer Vision and Pattern Recognition — 7 citations into it

Whom David Samuel trusts overall

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

1. Fabian-Robert Stöter
2. Naoya Takahashi
3. Yi Luo
4. Antoine Liutkus
5. Jen-Yu Liu
6. Daniel Stoller
7. Rajeev Ranjan
8. Francesc Lluís
9. Pritish Chandna
10. Michael Ruogu Zhang

Who trusts David Samuel overall

1. Naoya Takahashi
2. Alexandre D'efossez
3. Yuki Mitsufuji
4. Nicolas Usunier

Papers from David Samuel's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Learning Multiple Layers of Features from Tiny Images
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Meta-Learning Extractors for Music Source Separation (2020) — 68 citations