Duligur Ibeling

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it
• Safety, Robustness & Interpretability — 11 citations into it
• Causal Inference & Discovery — 10 citations into it
• Statistics and Probability — 10 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Duligur Ibeling trusts overall

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

1. Judea Pearl
2. Donald B. Rubin
3. Jin Tian
4. James M. Robins
5. Tom L. Burr
6. Xiaowei Huang
7. Robert L. Shook
8. Ilya Shpitser
9. Elias Bareinboim
10. R. H. Strotz

Papers from Duligur Ibeling's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Intriguing properties of neural networks
3. Causation, Prediction, and Search
4. Causal diagrams for empirical research
5. [On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9.] Comment: Neyman (1923) and Causal Inference in Experiments and Observational Studies
6. On the Testable Implications of Causal Models with Hidden Variables
7. Deep Learning
8. Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models
9. The central role of the propensity score in observational studies for causal effects
10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers

• The Marabou Framework for Verification and Analysis of Deep Neural Networks (2019) — 622 citations
• On Pearl’s Hierarchy and the Foundations of Causal Inference (2022) — 346 citations