1 code implementation • NeurIPS 2023 • Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish, Jean-Francois Ton
Off-Policy Evaluation (OPE) in contextual bandits is crucial for assessing new policies using existing data without costly experimentation.
1 code implementation • 17 Jan 2023 • Rob Cornish, Muhammad Faaiz Taufiq, Arnaud Doucet, Chris Holmes
We consider how to assess the accuracy of a digital twin using real-world data.
no code implementations • 9 Jun 2022 • Muhammad Faaiz Taufiq, Jean-Francois Ton, Rob Cornish, Yee Whye Teh, Arnaud Doucet
Most off-policy evaluation methods for contextual bandits have focused on the expected outcome of a policy, which is estimated via methods that at best provide only asymptotic guarantees.
1 code implementation • 5 Mar 2021 • Sahra Ghalebikesabi, Rob Cornish, Luke J. Kelly, Chris Holmes
We propose a variational autoencoder architecture to model both ignorable and nonignorable missing data using pattern-set mixtures as proposed by Little (1993).
1 code implementation • 10 Jul 2020 • Anthony Caterini, Rob Cornish, Dino Sejdinovic, Arnaud Doucet
Continuously-indexed flows (CIFs) have recently achieved improvements over baseline normalizing flows on a variety of density estimation tasks.
3 code implementations • ICML 2020 • Rob Cornish, Anthony L. Caterini, George Deligiannidis, Arnaud Doucet
We show that normalising flows become pathological when used to model targets whose supports have complicated topologies.
no code implementations • 25 Sep 2019 • Rob Cornish, Anthony Caterini, George Deligiannidis, Arnaud Doucet
We argue that flow-based density models based on continuous bijections are limited in their ability to learn target distributions with complicated topologies, and propose localised generative flows (LGFs) to address this problem.