Cmhnissan

https://arxiv.org › pdf
We introduced a novel causal discovery framework that bridges constraint based and gradient based continuous optimization methods through differentiable d separation

https://www.sciencedirect.com › science › article › pii › S...
A promising approach for creating machine learning models that inherently satisfy constraints after training is to encode background knowledge as explicit logical constraints that guide

https://cacm.acm.org › research › differentiable-economics...
Differentiable economics leverages machine learning and neural networks to tackle challenging problems in economics This approach transforms models of economic games and

https://link.springer.com › chapter
We explain our approach on a toy example in the domain of health care diagnostics and show that the use of domain constraints and a limited knowledge graph leads to better performance

https://www.sciencedirect.com › science › article › pii › S...
Participants could report explicit knowledge prior to reporting an intuition thus allowing for an empirical assessment of whether intuitions emerged before explicit knowledge

https://link.springer.com › article
This section introduces the novel concept of interventional constraints a new form of high level causal knowledge that expresses the expected direction and strength of causal effects between variable pairs

[url-7]
[desc-7]

[url-8]
[desc-8]

[url-9]
[desc-9]