Olof Mogren

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 2 papers; trusts 127 researchers and is trusted by 58 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Computer Vision and Pattern Recognition — 20 citations into it; #3,255 of 21,575 by trust here, #10,905 by citations
• Generative Models — 13 citations into it
• Model Architectures — 7 citations into it
• Optimization & Training — 5 citations into it
• Safety, Robustness & Interpretability — 5 citations into it
• Signal Processing — 5 citations into it; #312 of 7,572 by trust here, #2,664 by citations

Whom Olof Mogren trusts overall

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

1. Sepp Hochreiter
2. J. Urgen Schmidhuber
3. Ilya Sutskever
4. Alex Graves
5. Yoshua Bengio
6. Tomas Mikolov
7. Douglas Eck
8. Geoffrey E. Hinton
9. Tim Salimans
10. Oriol Vinyals

Who trusts Olof Mogren overall

1. Yongjun Hong
2. Eoin Brophy
3. Li-Chia Yang
4. Daniel Michelsanti
5. Hao-Wen Dong
6. Jean-Pierre Briot
7. Anne Marie Delaney
8. Abdul Jabbar
9. Jinsung Yoon
10. Hamed Alqahtani

Papers from Olof Mogren's perspective

Ordered by how strongly the researchers Olof Mogren 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. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• C-RNN-GAN: Continuous recurrent neural networks with adversarial training (2016) — 588 citations
• Adversarial representation learning for synthetic replacement of private attributes (2020) — 9 citations