Sarah Verhulst

Signal Processing · 2019

A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 14 citations into it; #4,947 of 7,572 by trust here, #7,112 by citations
• Generative Models — 11 citations into it
• Speech & Audio — 9 citations into it
• Artificial Intelligence — 8 citations into it
• Computational Mechanics — 6 citations into it; #6,663 of 10,001 by trust here, #9,276 by citations

Whom Sarah Verhulst trusts overall

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

1. Diederik P. Kingma
2. Christophe Veaux
3. Jimmy Ba
4. Cees H. Taal
5. Cassia Valentini-Botinhao
6. Junichi Yamagishi
7. Geoffrey E. Hinton

Who trusts Sarah Verhulst overall

1. Szu-Wei Fu

Papers from Sarah Verhulst's perspective

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

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

Their papers

• Sergan: Speech Enhancement Using Relativistic Generative Adversarial Networks with Gradient Penalty (2019) — 121 citations