Adrian Daniel Popescu

Artificial Intelligence · 2010–2021

A researcher in the Science corpus: 9 papers; trusts 969 researchers and is trusted by 185 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 171 citations into it; #1,702 of 35,345 by trust here, #4,336 by citations
• Computer Vision and Pattern Recognition — 161 citations into it; #2,652 of 21,575 by trust here, #3,659 by citations
• Meta & Continual Learning — 67 citations into it; #20 of 1,041 by trust here, #91 by citations
• Representation & Self-Supervised Learning — 63 citations into it
• Efficiency & Compression — 29 citations into it
• Evaluation & Benchmarks — 28 citations into it; #1,692 of 3,147 by trust here, #2,971 by citations
• Model Architectures — 28 citations into it
• Radiology, Nuclear Medicine and Imaging — 25 citations into it; #499 of 3,265 by trust here, #1,699 by citations

Whom Adrian Daniel Popescu trusts overall

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

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

Who trusts Adrian Daniel Popescu overall

1. Eden Belouadah
2. Tyler L. Hayes
3. Hongjoon Ahn
4. Da-Wei Zhou
5. Ali Ayub
6. Jaya Kalla
7. Marc Masana
8. Stefanie Nowak
9. Xialei Liu
10. Jhair Gallardo

Papers from Adrian Daniel Popescu's perspective

Ordered by how strongly the researchers Adrian Daniel Popescu 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
• Harnessing noisy Web images for deep representation (2017) — 13 citations
• Overview of the Wikipedia Image Retrieval Task at ImageCLEF 2011 (2011) — 49 citations
• Overview of the Wikipedia Retrieval Task at ImageCLEF 2010 (2010) — 52 citations