Gregor Wiedemann

Artificial Intelligence · 2012–2019

A researcher in the Science corpus: 3 papers; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 120 citations into it
• Natural Language Processing — 80 citations into it
• Information Systems — 27 citations into it
• Representation & Self-Supervised Learning — 23 citations into it
• Computer Vision and Pattern Recognition — 21 citations into it
• Large Language Models — 9 citations into it

Whom Gregor Wiedemann trusts overall

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

1. Geoffrey E. Hinton
2. Dekang Lin
3. Tomas Mikolov
4. Yoshua Bengio
5. Diederik P. Kingma
6. Ilya Sutskever
7. Alex Krizhevsky
8. Yann LeCun
9. Richard Socher
10. Jeffrey Pennington

Who trusts Gregor Wiedemann overall

1. Mario Giulianelli
2. Marco Del Tredici

Papers from Gregor Wiedemann's perspective

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

Their papers

• Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings (2019) — 201 citations
• Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology (2018) — 736 citations
• Fundamental Physics at the Intensity Frontier (2012) — 282 citations