Tobias Leemann
Artificial Intelligence · 2021–2022
A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 119 citations into it
- Computer Vision and Pattern Recognition — 54 citations into it
- Generative Models — 20 citations into it
- Large Language Models — 17 citations into it
- Model Architectures — 16 citations into it
- Optimization & Training — 12 citations into it
- Signal Processing — 8 citations into it
- Management Science and Operations Research — 7 citations into it
Whom Tobias Leemann trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Diederik P. Kingma
- Kaiming He
- Jerome H. Friedman
- Alec Radford
- Ilya Sutskever
- Yann LeCun
- Alex Graves
Who trusts Tobias Leemann overall
Papers from Tobias Leemann's perspective
Ordered by how strongly the researchers Tobias Leemann trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- GENERATIVE ADVERSARIAL NETS
Their papers
- Language Models are Realistic Tabular Data Generators (2022) — 423 citations
- Deep Neural Networks and Tabular Data: A Survey (2021) — 1,211 citations