Klas Leino

Artificial Intelligence · 2018–2021

A researcher in the Science corpus: 5 papers; trusts 230 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 97 citations into it; #13,869 of 35,345 by trust here, #13,544 by citations
• Safety, Robustness & Interpretability — 54 citations into it
• Computer Vision and Pattern Recognition — 48 citations into it
• Natural Language Processing — 16 citations into it
• Privacy & Security — 13 citations into it
• Model Architectures — 10 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Biophysics — 8 citations into it

Whom Klas Leino trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Karen Simonyan
6. Yoshua Bengio
7. Christian Szegedy
8. Ilya Sutskever
9. Kaiming He
10. Andrew Zisserman

Who trusts Klas Leino overall

1. Liwei Song
2. Lauren Watson
3. Nicholas Carlini
4. Angelina Wang
5. Sidak Pal Singh
6. Weichen Yu
7. Yujia Huang
8. Prateek Mittal
9. Melissa Hall
10. Zifan Wang

Papers from Klas Leino's perspective

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

Their papers

• Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference (2019) — 327 citations
• Feature-Wise Bias Amplification (2018) — 52 citations
• Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models (2020) — 10 citations
• Globally-Robust Neural Networks (2021) — 156 citations
• Influence-Directed Explanations for Deep Convolutional Networks (2018) — 80 citations