Romain Hennequin
Signal Processing · 2019–2020
A researcher in the Science corpus: 3 papers; trusts 15 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 18 citations into it; #3,855 of 7,572 by trust here, #6,591 by citations
- Artificial Intelligence — 9 citations into it; #26,948 of 35,345 by trust here, #33,294 by citations
- Speech & Audio — 6 citations into it
Whom Romain Hennequin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Fabian-Robert Stöter
- Andreas Jansson
- Laure Prétet
- Emmanuel Vincent
- Antoine Liutkus
- Diederik P. Kingma
- Rachel M. Bittner
- Eric J. Humphrey
- Jimmy Ba
- Stefan Uhlich
Who trusts Romain Hennequin overall
- Alexandre D'efossez
- Simon Rouard
- Prafulla Dhariwal
- Nicolas Usunier
- Francisco Massa
- L. Eon Bottou
- Anis Khlif
Papers from Romain Hennequin's perspective
Ordered by how strongly the researchers Romain Hennequin trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)