Nesterov-aided stochastic gradient methods using Laplace approximation for Bayesian design optimization

• Optimal experimental design
• Bayesian inference
• Laplace approximation
• Stochastic optimization
• Accelerated gradient descent
• Importance sampling

A Wasserstein Coupled Particle Filter for Multilevel Estimation

• filtering
• diffusions
• Multilevel Monte Carlo
• Particle Filters

A Derivative Tracking Model for Wind Power Forecast Error

• Wind power
• probabilistic forecasting
• Stochastic differential equations
• Lamperti transform,
• numerical optimization
• model selection
• time-inhomogeneous Jacobi diffusion

A Universal Splitting Estimator for the Performance Evaluation of Wireless Communications Systems

• rare event
• performance evaluation
• multilevel splitting algorithm
• variance reduction

Multilevel weighted least squares polynomial approximation

• Multilevel methods
• least squares approximation
• multivariate approximation
• polynomial approximation
• convergence rates
• error analysis

Multilevel Ensemble Kalman Filtering with local-level Kalman Gains

• Stochastic differential and integral equations
• Complexity and performance of numerical algorithms

Multilevel double loop Monte Carlo and stochastic collocation methods with importance sampling for Bayesian optimal experimental design

• Electrical impedance tomography
• Expected information gain
• Importance sampling
• multilevel
• Stochastic collocation

Solution of the 3D density-driven groundwater flow problem with uncertain porosity and permeability

• Uncertainty Quantification
• Density-driven flow
• Multigrid
• ug4
• Reservoir
• Groundwater
• Salt formations

Numerical smoothing and hierarchical approximations for efficient option pricing and density estimation

• Deterministic quadrature methods
• Hierarchical variance reduction methods
• Multilevel Monte Carlo
• Numerical smoothing
• Adaptive sparse grids quadrature
• Brownian bridge,
• Richardson extrapolation
• Option pricing
• Monte Carlo

Hierarchical adaptive sparse grids and quasi-Monte Carlo for option pricing under the rough Bergomi model

• Rough volatility
• Monte Carlo
• Adaptive sparse grids
• Quasi Monte Carlo
• Brownian bridge construction
• Richardson extrapolation

An Accurate Sample Rejection Estimator of the Outage Probability With Equal Gain Combining

• Outage probability
• equal gain combining
• Importance sampling
• sample rejection
• generalised selection combining
• bounded relative error

Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks

• Multilevel Monte Carlo
• Continuous time Markov chains
• Stochastic reaction networks
• Stochastic biological systems
• Importance sampling

Multilevel Ensemble Kalman filtering for spatially extended models

• Monte Carlo
• multilevel
• filtering
• Kalman filter
• ensemble Kalman filter

Weak error rates for option pricing under the rough Bergomi model

• Rough Bergomi
• Weak error rate

Smaller generalization error derived for deep compared to shallow residual neural networks

• residual network
• deep random feature
• supervised learning
• error estimates
• layer by layer algorithm

A note on tools for prediction under uncertainty and identifiability of SIR-like dynamical systems for epidemiology

• Dynamical Systems
• Mathematical Epidemiology
• Uncertainty Quantification
• Model Identifiability
• Bayesian Inversion
• Fisher Approximation

Efficient Importance Sampling for the Left Tail of Positive Gaussian Quadratic Forms

• Importance sampling
• left tail
• positive quadratic forms
• Gaussian random vector
• bounded relative error