Elahe Arani

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 6 papers; trusts 667 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 191 citations into it; #16,696 of 35,345 by trust here, #21,878 by citations
• Computer Vision and Pattern Recognition — 119 citations into it
• Meta & Continual Learning — 62 citations into it; #509 of 1,041 by trust here, #884 by citations
• Representation & Self-Supervised Learning — 61 citations into it
• Optimization & Training — 40 citations into it
• Safety, Robustness & Interpretability — 35 citations into it
• Cognitive Neuroscience — 18 citations into it; #5,513 of 10,852 by trust here, #8,086 by citations
• Efficiency & Compression — 17 citations into it

Whom Elahe Arani trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yann LeCun
5. Yoshua Bengio
6. Diederik P. Kingma
7. Alex Graves
8. Ilya Sutskever
9. Marc'Aurelio Ranzato
10. Christian Szegedy

Who trusts Elahe Arani overall

1. Prashant Bhat
2. Bahram Zonooz
3. Quang Pham
4. Liyuan Wang
5. Zhen Wang
6. Lorenzo Bonicelli
7. Yichen Wu
8. Chenghao Liu
9. Xingxing Zhang
10. Fahad Sarfraz

Papers from Elahe Arani's perspective

Ordered by how strongly the researchers Elahe Arani 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. ImageNet: A large-scale hierarchical image database
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. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Task-Aware Information Routing from Common Representation Space in Lifelong Learning (2023) — 36 citations
• Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System (2022) — 177 citations
• Task Agnostic Representation Consolidation: a Self-supervised based Continual Learning Approach (2022) — 16 citations
• Consistency is the key to further mitigating catastrophic forgetting in continual learning (2022) — 19 citations
• Knowledge Distillation Beyond Model Compression (2020) — 46 citations
• Noise as a Resource for Learning in Knowledge Distillation (2020) — 18 citations