Daniel Stoller

Signal Processing · 2018

A researcher in the Science corpus: 1 paper; trusts 23 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 12 citations into it; #1,771 of 7,572 by trust here, #2,664 by citations
• Speech & Audio — 7 citations into it; #390 of 1,076 by trust here, #628 by citations
• Computer Vision and Pattern Recognition — 5 citations into it

Whom Daniel Stoller trusts overall

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

1. Yi Luo
2. Emmanuel Vincent
3. Antoine Liutkus
4. Jonathan Le Roux
5. Daniel W. Griffin
6. Shrikant Venkataramani
7. Olaf Ronneberger
8. Santiago Pascual
9. Fabian-Robert Stöter
10. Dario Rethage

Who trusts Daniel Stoller overall

1. Jordi Pons
2. Alexandre D'efossez
3. Craig Macartney
4. Simon Rouard
5. David Samuel
6. Francesc Lluís
7. Alice Cohen-Hadria
8. Darius Petermann
9. Chitralekha Gupta
10. Shlomo E. Chazan

Papers from Daniel Stoller's perspective

Ordered by how strongly the researchers Daniel Stoller 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. GENERATIVE ADVERSARIAL NETS
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation (2018) — 709 citations