Alan Akbik

Artificial Intelligence · 2015–2019

A researcher in the Science corpus: 4 papers; trusts 89 researchers and is trusted by 62 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 56 citations into it; #13,429 of 35,345 by trust here, #15,236 by citations
• Natural Language Processing — 54 citations into it; #1,008 of 5,688 by trust here, #1,721 by citations
• Representation & Self-Supervised Learning — 19 citations into it
• Model Architectures — 13 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Evaluation & Benchmarks — 7 citations into it

Whom Alan Akbik trusts overall

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

1. Ilya Sutskever
2. Alex Graves
3. Sepp Hochreiter
4. Matthew E. Peters
5. Tomas Mikolov
6. Geoffrey E. Hinton
7. Yoshua Bengio
8. J. Urgen Schmidhuber
9. Diederik P. Kingma
10. Jeffrey Pennington

Who trusts Alan Akbik overall

1. Jinlan Fu
2. Xinyu Wang
3. Pengfei Liu
4. Jonas Pfeiffer
5. Branden Chan
6. Yufan Jiang
7. Yong Jiang
8. Ninareh Mehrabi
9. Han He
10. Wee Chung Gan

Papers from Alan Akbik's perspective

Ordered by how strongly the researchers Alan Akbik 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. 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP (2019) — 933 citations
• Generating High Quality Proposition Banks for Multilingual Semantic Role Labeling (2015) — 101 citations
• Pooled Contextualized Embeddings for Named Entity Recognition (2019) — 273 citations
• Contextual String Embeddings for Sequence Labeling (2018) — 1,382 citations