Ulli Waltinger

Artificial Intelligence · 2019

A researcher in the Science corpus: 3 papers; trusts 75 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 56 citations into it; #14,938 of 35,345 by trust here, #19,873 by citations
• Natural Language Processing — 50 citations into it; #2,748 of 5,688 by trust here, #3,897 by citations
• Representation & Self-Supervised Learning — 22 citations into it
• Large Language Models — 17 citations into it; #548 of 799 by trust here, #677 by citations
• Management Science and Operations Research — 6 citations into it

Whom Ulli Waltinger trusts overall

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

1. Diederik P. Kingma
2. Tomas Mikolov
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Ilya Sutskever
6. Jimmy Ba
7. Jacob Devlin
8. Alex Krizhevsky
9. John Wieting
10. Yann LeCun

Who trusts Ulli Waltinger overall

1. Zhengbao Jiang
2. Timo Schick
3. Tara Safavi
4. Nora Kassner
5. Hinrich Schütze
6. Ethan Perez
7. Katikapalli Subramanyam Kalyan
8. Zexuan Zhong
9. Yanai Elazar
10. Yanda Chen

Papers from Ulli Waltinger's perspective

Ordered by how strongly the researchers Ulli Waltinger trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Long Short-Term Memory
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet classification with deep convolutional neural networks
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
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

• E-BERT: Efficient-Yet-Effective Entity Embeddings for BERT (2019) — 168 citations
• Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity (2019) — 21 citations
• BERT is Not a Knowledge Base (Yet): Factual Knowledge vs. Name-Based Reasoning in Unsupervised QA (2019) — 80 citations