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@MShahriariNia You can use MLN for most problems where a probabilistic graphical model is suitable, a nice example: http://t.co/LH0rK87StN
@MShahriariNia You can use MLN for most problems where a probabilistic graphical model is suitable, a nice example: http://t.co/LH0rK87StN
@davidjayharris @twiecki See this example in bioinformatics http://t.co/vzk1ID87Pe 4/n
Interpretable ML output? http://t.co/nxjeIw0Yfs "achieves very good predictive performance while opening the door to some interpretability"
Learning a Markov Logic network for supervised gene regulatory network inference http://t.co/j5p3dsAhFJ #bmcbioinformatics