136 citations · 423 across the 42 of their papers we have counts for
8 papers · 1 filter
Adaptive stepsize algorithms for Langevin dynamics
Alix Leroy, Benedict Leimkuhler, Jonas Latz +1
We discuss the design of an invariant measure-preserving transformed dynamics for the numerical treatment of Langevin dynamics based on rescaling of time, with the goal of sampling…
Can We Rely on AI?
Desmond J. Higham
Over the last decade, adversarial attack algorithms have revealed instabilities in deep learning tools. These algorithms raise issues regarding safety, reliability and interpretabi…
A Personal Perspective on Numerical Analysis and Optimization
Desmond J. Higham
I give a brief, non-technical, historical perspective on numerical analysis and optimization. I also touch on emerging trends and future challenges. This content is based on the sh…
Accurate Computation of the Log-Sum-Exp and Softmax Functions
Pierre Blanchard, Desmond J. Higham, Nicholas J. Higham
Evaluating the log-sum-exp function or the softmax function is a key step in many modern data science algorithms, notably in inference and classification. Because of the exponentia…
Computational complexity analysis for Monte Carlo approximations of classically scaled population processes
David F. Anderson, Desmond J. Higham, Yu Sun
We analyze and compare the computational complexity of different simulation strategies for Monte Carlo in the setting of classically scaled population processes. This allows a rang…
An Introduction to Multilevel Monte Carlo for Option Valuation
Desmond J. Higham
Monte Carlo is a simple and flexible tool that is widely used in computational finance. In this context, it is common for the quantity of interest to be the expected value of a ran…