Amir-Hossein Karimi

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 6 papers; trusts 96 researchers and is trusted by 35 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 199 citations into it; #5,739 of 35,345 by trust here, #4,231 by citations
• Safety, Robustness & Interpretability — 94 citations into it
• AI Ethics, Fairness & Society — 47 citations into it
• Safety Research — 47 citations into it; #2,028 of 5,829 by trust here, #2,429 by citations
• Causal Inference & Discovery — 42 citations into it; #310 of 364 by trust here, #277 by citations
• Computer Vision and Pattern Recognition — 26 citations into it
• Natural Language Processing — 25 citations into it; #1,883 of 5,688 by trust here, #1,286 by citations
• Sociology and Political Science — 21 citations into it

Whom Amir-Hossein Karimi trusts overall

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

1. Judea Pearl
2. Bernhard Schölkopf
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Chris Russell
6. Yoshua Bengio
7. Alex Krizhevsky
8. L. Eon Bottou
9. Longbing Cao
10. Jan Peters

Who trusts Amir-Hossein Karimi overall

1. Julius von Kügelgen
2. Sahil Verma
3. Bernhard Schölkopf
4. Isabel Valera
5. Umang Bhatt
6. Ana Lucic
7. John P. Dickerson
8. Gilles Barthe
9. Vadim Borisov
10. Keegan E. Hines

Papers from Amir-Hossein Karimi's perspective

Ordered by how strongly the researchers Amir-Hossein Karimi 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. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
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. GENERATIVE ADVERSARIAL NETS

Their papers

• Key-Value Memory Networks for Directly Reading Documents (2016) — 1,081 citations
• Algorithmic recourse under imperfect causal knowledge: a probabilistic approach (2020) — 210 citations
• Algorithmic Recourse: from Counterfactual Explanations to Interventions (2020) — 456 citations
• A survey of algorithmic recourse: definitions, formulations, solutions, and prospects (2020) — 190 citations
• On the Fairness of Causal Algorithmic Recourse (2020) — 105 citations
• Model-Agnostic Counterfactual Explanations for Consequential Decisions (2019) — 405 citations