1 citations · 3 across the 10 of their papers we have counts for
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 Variational Autoencoders
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…
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…
Explainable Fraud Detection with Deep Symbolic Classification
Samantha Visbeek, Erman Acar, Floris den Hengst
There is a growing demand for explainable, transparent, and data-driven models within the domain of fraud detection. Decisions made by fraud detection models need to be explainable…