2 citations · 2 across the 3 of their papers we have counts for
3 papers
Fiaingen: A financial time series generative method matching real-world data quality
Jože M. Rožanec, Tina Žezlin, Laurentiu Vasiliu +3
Data is vital in enabling machine learning models to advance research and practical applications in finance, where accurate and robust models are essential for investment and tradi…
Causal Cartographer: From Mapping to Reasoning Over Counterfactual Worlds
Gaël Gendron, Jože M. Rožanec, Michael Witbrock +1
Causal world models are systems that can answer counterfactual questions about an environment of interest, i.e. predict how it would have evolved if an arbitrary subset of events h…
Counterfactual Causal Inference in Natural Language with Large Language Models
Gaël Gendron, Jože M. Rožanec, Michael Witbrock +1
Causal structure discovery methods are commonly applied to structured data where the causal variables are known and where statistical testing can be used to assess the causal relat…