#
tractable-models
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Sum-product networks in Julia.
machine-learning
deep-learning
julia
probabilistic-modeling
tractable-models
sum-product-networks
probabilistic-neural-network
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Updated
Aug 16, 2020 - Julia
A collection of commonly used datasets as benchmarks for density estimation in MaLe
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Updated
Jul 15, 2019 - Python
Probabilistic Circuits in Julia
julia
latent-variable-models
probabilistic-models
tractable-models
sum-product-networks
probabilistic-circuits
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Updated
Oct 13, 2020 - Julia
Cutset networks implementation in C++
machine-learning
generative-model
probabilistic-graphical-models
density-estimation
probabilistic-models
tractable-models
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Updated
Aug 12, 2018 - C++
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Currently user has to manually call MAR twice to get conditionals. Have some api like this:
Where
q_indices give indexes of variables inqfor each datapoint (all variables mentioned inq[i]should NOT be missing in the correspodingdata[i]). In the end we are computingp( q | x^o)for each