Bayesian Learning
A Bayesian network, Bayes network, belief network, Bayes(ian) model or probabilistic directed acyclic graphical model is a probabilistic graphical model (a type of statistical model) that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). (Wikipedia)
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BayesDAG: Gradient-Based Posterior Inference for Causal Discovery
Neural Information Processing Systems
In this work, we introduce a scalable Bayesian causal discovery framework based on a combination of stochastic gradient Markov Chain Monte Carlo (SG-MCMC) and V ariational Inference (VI) that overcomes these limitations.
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The Surprising Effectiveness of SP Voting with Partial Preferences
Neural Information Processing Systems
The SP algorithm requires the voters to predict other voters' report in the form of a full probability distribution over all rankings of alternatives.
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