Magdalena Biesialska

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 180 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 177 citations into it; #21,426 of 35,345 by trust here, #11,490 by citations
• Natural Language Processing — 109 citations into it; #3,650 of 5,688 by trust here, #3,369 by citations
• Computer Vision and Pattern Recognition — 83 citations into it; #13,305 of 21,575 by trust here, #11,083 by citations
• Evaluation & Benchmarks — 66 citations into it
• Meta & Continual Learning — 31 citations into it
• Representation & Self-Supervised Learning — 22 citations into it
• Optimization & Training — 12 citations into it
• Reinforcement Learning — 11 citations into it

Whom Magdalena Biesialska trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Ilya Sutskever
6. Yann LeCun
7. Marc'Aurelio Ranzato
8. Kaiming He
9. Arslan Chaudhry
10. L. Eon Bottou

Who trusts Magdalena Biesialska overall

1. Bo Liu
2. Aman Hussain
3. Martin Mundt
4. Yufan Huang
5. Thomas Scialom
6. Qian Liu
7. Nithin Holla
8. Da-Wei Zhou
9. Steven Braun
10. Christian Geishauser

Papers from Magdalena Biesialska's perspective

Ordered by how strongly the researchers Magdalena Biesialska 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Findings of the 2020 Conference on Machine Translation (WMT20) (2020) — 316 citations
• Continual Lifelong Learning in Natural Language Processing: A Survey (2020) — 272 citations
• Findings of the 2021 Conference on Machine Translation (WMT21) (2021) — 244 citations