Katarzyna Biesialska

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 172 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 109 citations into it; #21,427 of 35,345 by trust here, #16,471 by citations
• Computer Vision and Pattern Recognition — 65 citations into it; #13,306 of 21,575 by trust here, #11,083 by citations
• Natural Language Processing — 43 citations into it; #3,651 of 5,688 by trust here, #3,369 by citations
• Meta & Continual Learning — 31 citations into it
• Representation & Self-Supervised Learning — 21 citations into it
• Optimization & Training — 11 citations into it
• Reinforcement Learning — 11 citations into it
• Evaluation & Benchmarks — 10 citations into it

Whom Katarzyna 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. Yann LeCun
6. Ilya Sutskever
7. Marc'Aurelio Ranzato
8. Arslan Chaudhry
9. Kaiming He
10. L. Eon Bottou

Who trusts Katarzyna Biesialska overall

1. Bo Liu
2. Aman Hussain
3. Martin Mundt
4. Yufan Huang
5. Thomas Scialom

Papers from Katarzyna Biesialska's perspective

Ordered by how strongly the researchers Katarzyna 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. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Continual Lifelong Learning in Natural Language Processing: A Survey (2020) — 272 citations