3 papers
cs.LG2026
Neural Slack Variables for Shape Constraints
Ruben Wiedemann, Antoine Jacquier, Lukas Gonon
Enforcing functional inequality constraints such as monotonicity and convexity in neural networks is a fundamental challenge in many industrial and scientific applications. Classic…
cs.LG2026
Towards Continuous-time Causal Foundation Models
Dennis Thumm, Ruben Wiedemann, Ying Chen
Extending discrete-time causal Prior-data Fitted Networks for time series to continuous time invites writing the mechanism as a stochastic differential equation (SDE) -- but if the…
q-fin.CP2025
Operator Deep Smoothing for Implied Volatility
Ruben Wiedemann, Antoine Jacquier, Lukas Gonon
We devise a novel method for nowcasting implied volatility based on neural operators. Better known as implied volatility smoothing in the financial industry, nowcasting of implied…