Summary of On Discovery Of Local Independence Over Continuous Variables Via Neural Contextual Decomposition, by Inwoo Hwang et al.
On Discovery of Local Independence over Continuous Variables via Neural Contextual Decomposition
by Inwoo Hwang, Yunhyeok Kwak, Yeon-Ji Song, Byoung-Tak Zhang, Sanghack Lee
First submitted to arxiv on: 12 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (stat.ML)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a novel method, neural contextual decomposition (NCD), which learns a partition of the joint outcome space to discover multiple context-set specific independence (CSSI) relationships in a system. This is achieved by imposing each set to induce CSSI via modeling a conditional distribution. The proposed method successfully discovers the ground truth local independence relationships in both synthetic and complex systems reflecting real-world physical dynamics. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The researchers developed a new way to understand causal relationships between variables, which they call context-set specific independence (CSSI). They defined this relationship and showed how it can be used to discover multiple CSSI relationships in a system. To do this, they proposed a novel method called neural contextual decomposition (NCD), which learns the partition of the joint outcome space needed for this discovery. The researchers tested their method on both simple and complex systems and found that it successfully discovered the true causal relationships. |
