30 citations · 66 across the 16 of their papers we have counts for
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cs.LG2023★ 4 cited
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery
Yashas Annadani, Nick Pawlowski, Joel Jennings +3
Bayesian causal discovery aims to infer the posterior distribution over causal models from observed data, quantifying epistemic uncertainty and benefiting downstream tasks. However…
stat.ML2023★ 1 cited
Learnable Topological Features for Phylogenetic Inference via Graph Neural Networks
Cheng Zhang
Structural information of phylogenetic tree topologies plays an important role in phylogenetic inference. However, finding appropriate topological structures for specific phylogene…