Kanji Uchino

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it

Whom Kanji Uchino trusts overall

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

1. Elias Bareinboim
2. Judea Pearl
3. Leon A. Gatys

Papers from Kanji Uchino's perspective

Ordered by how strongly the researchers Kanji Uchino trusts endorse each paper. Same corpus, a different order for every researcher.

1. Causal inference and the data-fusion problem
2. Generative Adversarial Networks
3. Transportability of Causal Effects: Completeness Results
4. Counterfactual Fairness (Neural Information Processing Systems)
5. Image Style Transfer Using Convolutional Neural Networks
6. Image Analogies
7. The mythos of model interpretability
8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
9. Understanding Black-box Predictions via Influence Functions
10. ImageNet classification with deep convolutional neural networks

Their papers

• Biases in Generative Art: A Causal Look from the Lens of Art History (2020) — 85 citations
• Working with Beliefs: AI Transparency in the Enterprise (2018) — 43 citations