Eduardo Almeida Soares

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 6 papers; trusts 285 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 81 citations into it; #24,538 of 35,345 by trust here, #19,018 by citations
• Computer Vision and Pattern Recognition — 56 citations into it; #16,457 of 21,575 by trust here, #15,955 by citations
• Safety, Robustness & Interpretability — 27 citations into it; #1,782 of 2,251 by trust here, #1,975 by citations
• Model Architectures — 14 citations into it
• Health Informatics — 9 citations into it
• Media Technology — 8 citations into it
• Automotive Engineering — 6 citations into it; #2,740 of 3,081 by trust here, #2,851 by citations
• Evaluation & Benchmarks — 6 citations into it

Whom Eduardo Almeida Soares trusts overall

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

1. Plamen Parvanov Angelov
2. Xiaowei Gu
3. Mahdi Rezaei
4. Kaiming He
5. Karen Simonyan
6. Geoffrey E. Hinton
7. Alex Krizhevsky
8. Li Fei-Fei
9. Radford M. Neal
10. Christian Szegedy

Who trusts Eduardo Almeida Soares overall

1. Plamen Parvanov Angelov
2. Bo Li

Papers from Eduardo Almeida Soares's perspective

Ordered by how strongly the researchers Eduardo Almeida Soares trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Long Short-Term Memory
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Fair-by-design explainable models for prediction of recidivism (2019) — 25 citations
• Explainable artificial intelligence: an analytical review (2021) — 757 citations
• Towards Deep Machine Reasoning: a Prototype-based Deep Neural Network with Decision Tree Inference (2020) — 16 citations
• Towards Explainable Deep Neural Networks (xDNN) (2019) — 299 citations
• Actively Semi-Supervised Deep Rule-based Classifier Applied to Adverse Driving Scenarios (2019) — 16 citations
• Novelty Detection and Learning from Extremely Weak Supervision (2019) — 5 citations