Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The assessment of a probability distribution that is associated with a Bayesian network is a challenging task, even if its topology is sparse. Special probability distributions, based on the notion of causal independence, have therefore been proposed, as these allow defining a probability distribution in terms of Boolean combinations of local distributions. In Bayesian networks which need to model a large number of interactions among causal mechanisms even this approach becomes infeasible.  investigate the use of equivalence classes of binomial distributions as a means to define such very large Bayesian networks.
['Rasa Jurgelenaite', 'Peter J. F. Lucas']
I am writing a research paper on a idea Parameter estimation in large causal models
[{"from": "human", "value": "I am writing a research paper on a idea Parameter estimation in large causal models"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The assessment of a probability distribution that is associated with a Bayesian network is a challenging task, even if its topology is sparse. Special probability distributions, based on the notion of causal independence, have therefore been proposed, as these allow defining a probability distribution in terms of Boolean combinations of local distributions. In Bayesian networks which need to model a large number of interactions among causal mechanisms even this approach becomes infeasible.  investigate the use of equivalence classes of binomial distributions as a means to define such very large Bayesian networks."}]