37 citations · 188 across the 16 of their papers we have counts for
Showing 2020Show all
2 papers · 1 filter
cs.LG2020★ 4 cited
Towards Scalable Bayesian Learning of Causal DAGs
Jussi Viinikka, Antti Hyttinen, Johan Pensar +1
We give methods for Bayesian inference of directed acyclic graphs, DAGs, and the induced causal effects from passively observed complete data. Our methods build on a recent Markov…
stat.CO2020★ 4 cited
High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood
Kimmo Suotsalo, Yingying Xu, Jukka Corander +1
Learning vector autoregressive models from multivariate time series is conventionally approached through least squares or maximum likelihood estimation. These methods typically ass…