Bahram Zonooz

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; #16,695 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; #508 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; #5,512 of 10,852 by trust here, #8,086 by citations
• Efficiency & Compression — 17 citations into it

Whom Bahram Zonooz trusts overall

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

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

Who trusts Bahram Zonooz overall

1. Elahe Arani
2. Prashant Bhat
3. Quang Pham
4. Liyuan Wang

Papers from Bahram Zonooz's perspective

Ordered by how strongly the researchers Bahram Zonooz 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. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
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