Esteban Real
Artificial Intelligence · 2014–2023
A researcher in the Science corpus: 9 papers; trusts 763 researchers and is trusted by 1,817 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 287 citations into it; #862 of 35,345 by trust here, #1,101 by citations
- Computer Vision and Pattern Recognition — 235 citations into it; #966 of 21,575 by trust here, #956 by citations
- Model Architectures — 107 citations into it
- Optimization & Training — 94 citations into it; #324 of 2,601 by trust here, #220 by citations
- Evaluation & Benchmarks — 61 citations into it; #1,121 of 3,147 by trust here, #970 by citations
- Neural Architecture Search & AutoML — 56 citations into it; #126 of 283 by trust here, #70 by citations
- Natural Language Processing — 43 citations into it
- Reinforcement Learning — 35 citations into it
Whom Esteban Real trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Yoshua Bengio
- Christian Szegedy
- Ilya Sutskever
- Barret Zoph
- Yann LeCun
- Quoc V. Le
- Karen Simonyan
Who trusts Esteban Real overall
- Xuanyi Dong
- Quoc V. Le
- Colin White
- Frank Hutter
- Hanxiao Liu
- Arber Zela
- Thomas Elsken
- Yanan Sun
- Hang Xu
- Barret Zoph
Papers from Esteban Real's perspective
Ordered by how strongly the researchers Esteban Real trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Regularized Evolution for Image Classifier Architecture Search (2018) — 3,377 citations
- Large-Scale Evolution of Image Classifiers (2017) — 1,766 citations
- YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video (2017) — 577 citations
- Attention for Fine-Grained Categorization (2014) — 160 citations
- NAS-Bench-101: Towards Reproducible Neural Architecture Search (2019) — 821 citations
- AutoML-Zero: Evolving Machine Learning Algorithms From Scratch (2020) — 280 citations
- Symbolic Discovery of Optimization Algorithms (2023) — 679 citations
- Aging Evolution for Image Classifier Architecture Search (2019) — 96 citations
- Evolving Reinforcement Learning Algorithms (2021) — 84 citations