Ondřej Cífka

Artificial Intelligence · 2018–2021

A researcher in the Science corpus: 3 papers; trusts 238 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 70 citations into it; #30,668 of 35,345 by trust here, #21,316 by citations
• Computer Vision and Pattern Recognition — 55 citations into it
• Natural Language Processing — 47 citations into it
• Model Architectures — 28 citations into it
• Generative Models — 13 citations into it
• Representation & Self-Supervised Learning — 11 citations into it
• Evaluation & Benchmarks — 7 citations into it; #2,624 of 3,147 by trust here, #2,545 by citations

Whom Ondřej Cífka trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Ilya Sutskever
4. Yoshua Bengio
5. Kyunghyun Cho
6. Alex Krizhevsky
7. Dzmitry Bahdanau
8. Yann LeCun
9. Oriol Vinyals
10. Alex Graves

Who trusts Ondřej Cífka overall

1. Dan Friedman
2. David Marecek
3. Bo Pang
4. Junbo Jake Zhao
5. Mehdi S. M. Sajjadi
6. Adji Bousso Dieng
7. H. Çelikkanat
8. Kellie Webster
9. Tian Han
10. Yoon Kim

Papers from Ondřej Cífka's perspective

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

Their papers

• Eval all, trust a few, do wrong to none: Comparing sentence generation models (2018) — 41 citations
• Relative Positional Encoding for Transformers with Linear Complexity (2021) — 64 citations
• Are BLEU and Meaning Representation in Opposition? (2018) — 18 citations