Nils Holzenberger
Natural Language Processing · with Durme · 2019–2020
A researcher in the Science corpus: 2 papers; trusts 33 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 54 citations into it; #4,379 of 5,688 by trust here, #5,214 by citations
- Artificial Intelligence — 51 citations into it; #22,364 of 35,345 by trust here, #23,077 by citations
- Computer Vision and Pattern Recognition — 19 citations into it
- Large Language Models — 5 citations into it
- Representation & Self-Supervised Learning — 5 citations into it
Whom Nils Holzenberger trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Sergey Ioffe
- Jacob Devlin
- Jimmy Ba
- Geoffrey E. Hinton
- Christian Szegedy
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
Who trusts Nils Holzenberger overall
Papers from Nils Holzenberger's perspective
Ordered by how strongly the researchers Nils Holzenberger trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering (2020) — 88 citations
- Large-Scale, Diverse, Paraphrastic Bitexts via Sampling and Clustering (2019) — 70 citations