Feb. 26, 2024, 5:44 a.m. | Kevin Xia, Elias Bareinboim

cs.LG updates on arXiv.org arxiv.org

arXiv:2401.02602v2 Announce Type: replace
Abstract: The abilities of humans to understand the world in terms of cause and effect relationships, as well as to compress information into abstract concepts, are two hallmark features of human intelligence. These two topics have been studied in tandem in the literature under the rubric of causal abstractions theory. In practice, it remains an open problem how to best leverage abstraction theory in real-world causal inference tasks, where the true mechanisms are unknown and only …

abstract abstractions arxiv cause and effect concepts cs.ai cs.lg features hallmark human human intelligence humans information intelligence literature practice relationships terms theory topics type world

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US