31 citations · 152 across the 38 of their papers we have counts for
9 papers · 1 filter
Arbitrage-Aware Probabilistic Multi-Step Forecasting of Implied Volatility Surfaces: Joint Generation of Surface-Return Trajectories Using Latent Diffusion
Dominik Manuel Buchegger, Lukas Gonon
Implied volatility surfaces summarise the option market and are central to many financial applications. Probabilistic forecasting of their future evolution requires modelling two-d…
Robust Control under Stationary Ambiguity
Konrad J. Mueller, Amira Akkari, Ben Wood +1
Control policies optimized in simulation can perform poorly in the real system when the parameters of the simulator are estimated from limited data but the resulting parameter…
Universality and Approximation Rates of Graph Neural Networks with Random Features
Lukas Gonon, Thilo Meyer-Brandis, Niklas Weber
We investigate message-passing graph neural networks with random node features. Random node features are known to enhance the expressiveness of graph neural networks (GNNs) both th…
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…
Generating Financial Time Series by Matching Random Convolutional Features
Konrad J. Mueller, Nikita Zozoulenko, Ben Wood +2
Generating realistic financial time series is challenging as training data is often limited to a single historical path. With such scarce data, overfitting is hard to avoid, especi…
Random Neural Network Expressivity for Non-Linear Partial Differential Equations
Muhammed Ali Mehmood, Lukas Gonon
Neural networks with randomly generated hidden weights (RaNNs) have been extensively studied, both as a standalone learning method and as an initialization for fully trainable deep…