Plamen Parvanov Angelov

Artificial Intelligence · 2004–2021

A researcher in the Science corpus: 13 papers; trusts 556 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 79 citations into it; #4,899 of 35,345 by trust here, #10,207 by citations
• Computer Vision and Pattern Recognition — 79 citations into it; #13,034 of 21,575 by trust here, #15,162 by citations
• Safety, Robustness & Interpretability — 27 citations into it; #1,783 of 2,251 by trust here, #1,975 by citations
• Media Technology — 19 citations into it; #2,549 of 3,621 by trust here, #3,522 by citations
• Model Architectures — 18 citations into it
• Statistics and Probability — 14 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Health Informatics — 9 citations into it

Whom Plamen Parvanov Angelov trusts overall

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

1. Karen Simonyan
2. Yann LeCun
3. Kaiming He
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. David Ruppert
7. Andrew Zisserman
8. Yoshua Bengio
9. Radford M. Neal
10. Christian Szegedy

Who trusts Plamen Parvanov Angelov overall

1. Eduardo Almeida Soares
2. Xiaowei Gu
3. Bruno Costa
4. J. J. Rubio
5. Edwin David Lughofer
6. Hai-Jun Rong
7. Santiago Marco
8. Chia-Feng Juang
9. Marcos Castro
10. Subramanya P. Nageshrao

Papers from Plamen Parvanov Angelov's perspective

Ordered by how strongly the researchers Plamen Parvanov Angelov 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
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
• A Generalized Methodology for Data Analysis (2018) — 71 citations
• Empirical Approach to Machine Learning (2018) — 80 citations
• Deep rule-based classifier with human-level performance and characteristics (2018) — 63 citations
• Autonomous Learning Systems: From Data Streams to Knowledge in Real-time (2013) — 201 citations
• Evolving Intelligent Systems: Methodology and Applications (2010) — 323 citations
• Evolving Fuzzy-Rule-Based Classifiers From Data Streams (2008) — 389 citations
• An approach to online identification of Takagi-Sugeno fuzzy models (2004) — 1,006 citations