Leonard Salewski

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 176 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 80 citations into it; #31,636 of 35,345 by trust here, #23,731 by citations
• Computer Vision and Pattern Recognition — 55 citations into it; #19,460 of 21,575 by trust here, #15,529 by citations
• Natural Language Processing — 24 citations into it
• Representation & Self-Supervised Learning — 22 citations into it
• Evaluation & Benchmarks — 15 citations into it; #2,711 of 3,147 by trust here, #2,799 by citations
• Graph Learning — 5 citations into it

Whom Leonard Salewski trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Yoshua Bengio
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Ilya Sutskever
7. Yann LeCun
8. Ruslan Salakhutdinov
9. Oriol Vinyals
10. Ross B. Girshick

Who trusts Leonard Salewski overall

1. Hoang Nguyen
2. Congying Xia
3. Bodhisattwa Prasad Majumder
4. Anna Kukleva

Papers from Leonard Salewski's perspective

Ordered by how strongly the researchers Leonard Salewski 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. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks (2021) — 118 citations
• Relational Generalized Few-Shot Learning (2019) — 27 citations