3 citations · 4 across the 4 of their papers we have counts for
3 papers · 1 filter
Improving the Efficiency of the PC Algorithm by Using Model-Based Conditional Independence Tests
Erica Cai, Andrew McGregor, David Jensen
Learning causal structure is useful in many areas of artificial intelligence, including planning, robotics, and explanation. Constraint-based structure learning algorithms such as…
Measuring Interventional Robustness in Reinforcement Learning
Katherine Avery, Jack Kenney, Pracheta Amaranath +2
Recent work in reinforcement learning has focused on several characteristics of learned policies that go beyond maximizing reward. These properties include fairness, explainability…
Causal Discovery for Manufacturing Domains
Katerina Marazopoulou, Rumi Ghosh, Prasanth Lade +1
Yield and quality improvement is of paramount importance to any manufacturing company. One of the ways of improving yield is through discovery of the root causal factors affecting…