Risk

Automatic implicit function theorem

Dmitri Goloubentsev, Evgeny Lakshtanov and Vladimir Piterbarg explain in mathematical terms, and demonstrate using a simple example, how the automatic implicit function theorem, a special version of ...
Risk

Adjoint algorithmic differentiation: calibration and implicit function theorem

Adjoint algorithmic differentiation is an efficient way to obtain financial instrument price derivatives with respect to the data inputs. Often the differentiation does not cover the full pricing ...
GitHub

Few-shot Implicit Function Generation via Equivariance

Implicit Neural Representations (INRs) have emerged as a powerful framework for representing continuous signals. However, generating diverse INR weights remains challenging due to limited training ...
IEEE

Delay/Disturbance-Tolerant Finite-Time Stabilization for Linear Systems: Inverse-Optimal Implicit-Lyapunov-Function Approach

Abstract: For a class of input-delayed disturbed linear systems, this paper considers the problem of finite-time implicit-Lyapunov-function (ILF)-based control. With ILF as the evaluation of system ...