4 papers · 1 filter
Amortized Interventional Forecasting for Multivariate CIR Processes
Andreas Sauter, Sumit Sourabh, Drona Kandhai +1
Mean-reverting dynamics are pervasive in finance, and the Cox--Ingersoll--Ross (CIR) process is a standard model for the time series they produce, from short rates to credit defaul…
ACTIVA: Amortized Causal Effect Estimation via Transformer-based Variational Autoencoder
Andreas Sauter, Saber Salehkaleybar, Frank van Harmelen +2
Predicting post-intervention distributions from observational data is central to many scientific and decision-making problems, but remains challenging due to causal ambiguity, rest…
EduGym: An Environment and Notebook Suite for Reinforcement Learning Education
Thomas M. Moerland, Matthias Müller-Brockhausen, Zhao Yang +7
Due to the empirical success of reinforcement learning, an increasing number of students study the subject. However, from our practical teaching experience, we see students enterin…
CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
Andreas W. M. Sauter, Nicolò Botteghi, Erman Acar +1
Causal discovery is the challenging task of inferring causal structure from data. Motivated by Pearl's Causal Hierarchy (PCH), which tells us that passive observations alone are no…