Damien Dablain

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 97 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Generative Models — 15 citations into it
• Optimization & Training — 11 citations into it
• Electrical and Electronic Engineering — 6 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Damien Dablain trusts overall

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

1. Diederik P. Kingma
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Kaiming He
5. Yann LeCun
6. Yoshua Bengio
7. Sergey Ioffe
8. Christian Szegedy
9. Vinod Nair
10. Jimmy Ba

Papers from Damien Dablain's perspective

Ordered by how strongly the researchers Damien Dablain 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data (2021) — 502 citations