Eden Belouadah

Artificial Intelligence · 2018–2021

A researcher in the Science corpus: 6 papers; trusts 805 researchers and is trusted by 178 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 143 citations into it; #1,703 of 35,345 by trust here, #4,393 by citations
• Computer Vision and Pattern Recognition — 124 citations into it; #2,666 of 21,575 by trust here, #3,747 by citations
• Meta & Continual Learning — 67 citations into it; #21 of 1,041 by trust here, #91 by citations
• Representation & Self-Supervised Learning — 48 citations into it
• Efficiency & Compression — 28 citations into it
• Radiology, Nuclear Medicine and Imaging — 25 citations into it; #500 of 3,265 by trust here, #1,699 by citations
• Evaluation & Benchmarks — 21 citations into it
• Optimization & Training — 20 citations into it

Whom Eden Belouadah trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Max Welling
5. X. Zhang
6. Yoshua Bengio
7. Ross B. Girshick
8. Shaoqing Ren
9. Diederik P. Kingma
10. Yann LeCun

Who trusts Eden Belouadah overall

1. Tyler L. Hayes
2. Adrian Daniel Popescu
3. Hongjoon Ahn
4. Da-Wei Zhou
5. Ali Ayub
6. Marc Masana
7. Jaya Kalla
8. Xialei Liu
9. Jhair Gallardo
10. Arthur Douillard

Papers from Eden Belouadah's perspective

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

Their papers

• IL2M: Class Incremental Learning With Dual Memory (2019) — 393 citations
• Avalanche: an End-to-End Library for Continual Learning (2021) — 219 citations
• A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks (2020) — 259 citations
• Initial Classifier Weights Replay for Memoryless Class Incremental Learning (2020) — 24 citations
• ScaIL: Classifier Weights Scaling for Class Incremental Learning (2020) — 90 citations
• DeeSIL: Deep-Shallow Incremental Learning (2018) — 77 citations