Saeid Nahavandi

Artificial Intelligence · 2004–2023

A researcher in the Science corpus: 16 papers; trusts 546 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 299 citations into it; #18,674 of 35,345 by trust here, #13,353 by citations
• Computer Vision and Pattern Recognition — 261 citations into it
• Reinforcement Learning — 102 citations into it
• Probabilistic & Bayesian Methods — 58 citations into it
• Control and Systems Engineering — 57 citations into it
• Generative Models — 48 citations into it
• Safety, Robustness & Interpretability — 33 citations into it
• Model Architectures — 30 citations into it

Whom Saeid Nahavandi trusts overall

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

1. Geoffrey E. Hinton
2. Radford M. Neal
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Richard S. Sutton
6. Yoshua Bengio
7. Kaiming He
8. Yann LeCun
9. Michael I. Jordan
10. Ilya Sutskever

Who trusts Saeid Nahavandi overall

1. Amr Adel
2. Hao Quan
3. Tim Pearce
4. Shutao Li
5. Jieyi Long
6. Thanh Thi Nguyen
7. Wei Tang
8. Elias G. Carayannis
9. Mohammad Haghighat
10. Yu Liu

Papers from Saeid Nahavandi's perspective

Ordered by how strongly the researchers Saeid Nahavandi 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Deep learning for deepfakes creation and detection: A survey (2019) — 629 citations
• Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and Applications (2018) — 1,032 citations
• Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances (2011) — 640 citations
• Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals (2011) — 707 citations
• A New Tensioning Method using Deep Reinforcement Learning for Surgical Pattern Cutting (2019) — 42 citations
• Industry 5.0—A Human-Centric Solution (2019) — 1,162 citations
• A Survey of Imitation Learning: Algorithms, Recent Developments, and Challenges (2023) — 329 citations
• Epileptic Seizures Detection Using Deep Learning Techniques: A Review (2020) — 385 citations
• A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges (2020) — 2,678 citations
• Deep Learning for Deepfakes Creation and Detection (2019) — 150 citations
• Synchronization of an Inertial Neural Network With Time-Varying Delays and Its Application to Secure Communication (2018) — 308 citations
• Extreme learning machine based transfer learning algorithms: A survey (2017) — 79 citations
• Dynamic Nanofin Heat Sinks (2014) — 235 citations
• Comments on 'Information measure for performance of image fusion' (2008) — 455 citations
• Asymmetrical three-DOFs rotational-translational parallel-kinematics mechanisms based on lie group theory (2006) — 54 citations
• Characterization of conducting polymer coated synthetic fabrics for heat generation (2004) — 153 citations