Ciarán M. Lee

Artificial Intelligence · 2015–2021

A researcher in the Science corpus: 5 papers; trusts 25 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 98 citations into it
• Atomic and Molecular Physics, and Optics — 33 citations into it; #5,152 of 7,135 by trust here, #7,069 by citations
• Causal Inference & Discovery — 25 citations into it
• Probabilistic & Bayesian Methods — 20 citations into it
• Statistics and Probability — 16 citations into it
• History and Philosophy of Science — 8 citations into it; #397 of 602 by trust here, #571 by citations
• Management Science and Operations Research — 8 citations into it
• Philosophy — 8 citations into it

Whom Ciarán M. Lee trusts overall

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

1. Judea Pearl
2. J. Gerring
3. Rafael Chaves
4. David E. Heckerman
5. Ilya Shpitser
6. Jan Peters
7. Quaid D. Morris
8. Dominik Janzing
9. Daniel Nikolaev Nikovski
10. Robert W. Spekkens

Who trusts Ciarán M. Lee overall

1. Jonathan G. Richens
2. Saurabh Johri

Papers from Ciarán M. Lee's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Causality : Models , Reasoning , and Inference
7. Probabilistic reasoning in intelligent systems: Networks of plausible inference
8. Learning Multiple Layers of Features from Tiny Images
9. Attention is All you Need (Neural Information Processing Systems)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Improving the accuracy of medical diagnosis with causal machine learning (2020) — 557 citations
• Causal Inference via Algebraic Geometry: Feasibility Tests for Functional Causal Structures with Two Binary Observed Variables (2015) — 45 citations
• Author Correction: Improving the accuracy of medical diagnosis with causal machine learning (2021) — 11 citations
• MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming (2019) — 19 citations
• Quantum common causes and quantum causal models (2016) — 227 citations