Payam M. Barnaghi

Artificial Intelligence · 2012–2019

A researcher in the Science corpus: 4 papers; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 57 citations into it
• Computer Vision and Pattern Recognition — 34 citations into it
• Model Architectures — 18 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Information Systems — 12 citations into it
• Statistical Learning Theory — 12 citations into it
• Statistics and Probability — 9 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it

Whom Payam M. Barnaghi trusts overall

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

1. Geoffrey E. Hinton
2. Douglas A. Reynolds
3. Radford M. Neal
4. Alex Krizhevsky
5. Yann LeCun
6. Yoshua Bengio
7. Friedemann Zenke
8. Nitin Kamra
9. J. Urgen Schmidhuber
10. Kaiming He

Who trusts Payam M. Barnaghi overall

1. Lea Duncker

Papers from Payam M. Barnaghi's perspective

Ordered by how strongly the researchers Payam M. Barnaghi 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. Gradient-based learning applied to document recognition
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Continual Learning in Deep Neural Network by Using a Kalman Optimiser (2019) — 5 citations
• Continual Learning Using Bayesian Neural Networks (2019) — 46 citations
• Machine learning for Internet of Things data analysis: A survey (2017) — 970 citations
• The SSN ontology of the W3C semantic sensor network incubator group (2012) — 1,559 citations