9 citations · 13 across the 15 of their papers we have counts for
19 papers
Single- and Multilevel Quadrature with Error Control for Fourier Pricing under the Rough Heston Model
Chiheb Ben Hammouda, Abderrahmene Ben Romdhane, Michael Samet +1
Unlike the classical Heston model, Fourier pricing under the rough Heston model requires solving a fractional Riccati equation at every quadrature point. Since the required resolut…
Pontryagin-Based Solver with Smoothed Hamiltonian, Adaptive , and PA-Bundle Refinement
Salim Ksous, Sebastian Lalvay Segovia, Mattias Sandberg +3
We present a Pontryagin-based numerical solver for deterministic optimal control problems in Bolza form. The solver regularizes the generally nonsmooth Hamiltonian using a log-sum-…
Data-Driven Stochastic Optimal Control for Intraday Electricity Trading by Renewable Producers
Chiheb Ben Hammouda, Michael Samet, Raul Tempone
The rapid growth of weather-dependent renewable generation increases price volatility and imbalance penalty risk in power markets, creating the need for advanced quantitative tradi…
A Pontryagin Maximum Principle on the Belief Space for Continuous-Time Optimal Control with Discrete Observations
Christian Bayer, Saifeddine Ben naamia, Erik von Schwerin +1
We study a continuous time stochastic optimal control problem under partial observations that are available only at discrete time instants. This hybrid setting, with continuous dyn…
Hierarchical Importance Sampling for Estimating Occupation Time for SDE Solutions
Eya Ben Amar, Nadhir Ben Rached, Raul Tempone
This study considers the estimation of the complementary cumulative distribution function of the occupation time (i.e., the time spent below a threshold) for a process governed by…
Convergence for adaptive resampling of random Fourier features
Xin Huang, Aku Kammonen, Anamika Pandey +4
The machine learning random Fourier feature method for data in high dimension is computationally and theoretically attractive since the optimization is based on a convex standard l…
Goal-Oriented Adaptive Finite Element Multilevel Quasi-Monte Carlo
Joakim Beck, Yang Liu, Erik von Schwerin +1
The efficient approximation of quantities of interest derived from PDEs with lognormal diffusivity is a central challenge in uncertainty quantification. This paper targets a proble…
An Adaptive Random Fourier Features approach Applied to Learning Stochastic Differential Equations
Owen Douglas, Aku Kammonen, Anamika Pandey +1
This work proposes a training algorithm based on adaptive random Fourier features (ARFF) with Metropolis sampling and resampling \cite{kammonen2024adaptiverandomfourierfeatures} fo…
Optimal power procurement for green cellular wireless networks under uncertainty and chance constraints
Nadhir Ben Rached, Shyam Mohan Subbiah Pillai, Raúl Tempone
Given the increasing global emphasis on sustainable energy usage and the rising energy demands of cellular wireless networks, this work seeks an optimal short-term, continuous-time…
Filtered Markovian Projection: Dimensionality Reduction in Filtering for Stochastic Reaction Networks
Chiheb Ben Hammouda, Maksim Chupin, Sophia Münker +1
Stochastic reaction networks (SRNs) model stochastic effects for various applications, including intracellular chemical or biological processes and epidemiology. A typical challeng…
Adaptive Random Fourier Features Training Stabilized By Resampling With Applications in Image Regression
Aku Kammonen, Anamika Pandey, Erik von Schwerin +1
This paper presents an enhanced adaptive random Fourier features (ARFF) training algorithm for shallow neural networks, building upon the work introduced in "Adaptive Random Fourie…
Forward Propagation of Low Discrepancy Through McKean-Vlasov Dynamics: From QMC to MLQMC
Nadhir Ben Rached, Abdul-Lateef Haji-Ali, Raúl Tempone +1
This work develops a particle system addressing the approximation of McKean-Vlasov stochastic differential equations (SDEs). The novelty of the approach lies in involving low discr…
Continuous time Stochastic optimal control under discrete time partial observations
Christian Bayer, Boualem Djehiche, Eliza Rezvanova +1
This work addresses stochastic optimal control problems where the unknown state evolves in continuous time while partial, noisy, and possibly controllable measurements are only ava…
Importance sampling for rare event tracking within the ensemble Kalman filtering framework
Nadhir Ben Rached, Erik von Schwerin, Gaukhar Shaimerdenova +1
In this work we employ importance sampling (IS) techniques to track a small over-threshold probability of a running maximum associated with the solution of a stochastic differentia…
Quasi-Monte Carlo with Domain Transformation for Efficient Fourier Pricing of Multi-Asset Options
Christian Bayer, Chiheb Ben Hammouda, Antonis Papapantoleon +2
Efficiently pricing multi-asset options poses a significant challenge in quantitative finance. Fourier methods leverage the regularity properties of the integrand in the Fourier do…
Comparing Spectral Bias and Robustness For Two-Layer Neural Networks: SGD vs Adaptive Random Fourier Features
Aku Kammonen, Lisi Liang, Anamika Pandey +1
We present experimental results highlighting two key differences resulting from the choice of training algorithm for two-layer neural networks. The spectral bias of neural networks…
Lagrangian Relaxation for Continuous-Time Optimal Control of Coupled Hydrothermal Power Systems Including Storage Capacity and a Cascade of Hydropower Systems with Time Delays
Chiheb Ben Hammouda, Eliza Rezvanova, Erik von Schwerin +1
This work considers a short-term, continuous time setting characterized by a coupled power supply system controlled exclusively by a single provider and comprising a cascade of hyd…
Residual Multi-Fidelity Neural Network Computing
Owen Davis, Mohammad Motamed, Raul Tempone
In this work, we consider the general problem of constructing a neural network surrogate model using multi-fidelity information. Motivated by error-complexity estimates for ReLU ne…
An Efficient Forward-Reverse Expectation-Maximization Algorithm for Statistical Inference in Stochastic Reaction Networks
Christian Bayer, Alvaro Moraes, Raul Tempone +1
In this work, we present an extension to the context of Stochastic Reaction Networks (SRNs) of the forward-reverse representation introduced in "Simulation of forward-reverse stoch…