Work #1 explores #kernel methods for bivariate causal discovery using Conditional Mean Embedding (CME).
A parsimony-based method helps infer causal direction by comparing complexity measures of CME sets. 📊 #KernelMethods#CausalDiscovery Great collab with @sejDino
Yesterday was a day very much circling around notions of quantum-assisted machine learning. After #QTML2021, Sofiene Jerbi from Innsbruck gave a wonderful talk on #quantummachinelearning beyond #kernelmethods in our reading group.