19 citations · 23 across the 8 of their papers we have counts for
4 papers · 1 filter
BLOB : A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals
Otmane Sakhi, Stephen Bonner, David Rohde +1
A common task for recommender systems is to build a pro le of the interests of a user from items in their browsing history and later to recommend items to the user from the same ca…
Causal inference with Bayes rule
Finnian Lattimore, David Rohde
The concept of causality has a controversial history. The question of whether it is possible to represent and address causal problems with probability theory, or if fundamentally n…
Reconsidering Analytical Variational Bounds for Output Layers of Deep Networks
Otmane Sakhi, Stephen Bonner, David Rohde +1
The combination of the re-parameterization trick with the use of variational auto-encoders has caused a sensation in Bayesian deep learning, allowing the training of realistic gene…
A Bayesian Solution to the M-Bias Problem
David Rohde
It is common practice in using regression type models for inferring causal effects, that inferring the correct causal relationship requires extra covariates are included or ``adjus…