Results 21 to 30 of about 209 (114)

Adaptive Sliding‐Mode Control of a Perturbed Diffusion Process With Pointwise In‐Domain Actuation

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT A sliding mode–based adaptive control law is proposed for a class of diffusion processes featuring a spatially‐varying uncertain diffusivity and equipped with several point‐wise actuators located at the two boundaries of the spatial domain as well as in its interior.
Paul Mayr   +3 more
wiley   +1 more source

Feedback Linearisation with State Constraints

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Feedback Linearisation (FBL) is a widely used technique that applies feedback laws to transform input‐affine nonlinear control systems into linear control systems, allowing for the use of linear controller design methods such as pole placement.
Songlin Jin, Yuanbo Nie, Morgan Jones
wiley   +1 more source

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

open access: yesComputer Graphics Forum, EarlyView.
We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier   +5 more
wiley   +1 more source

Existence and Uniqueness of Non-linear, Possibly Degenerate Parabolic PDEs, with Applications to Flow in Porous Media [PDF]

open access: yes, 2017
In the branch of mathematical analysis known as functional analysis, one mainly studies functions defined on vector spaces. For partial differential equations (PDEs), this analysis has proven to be a mighty resource of understanding and modelling the ...
Westrheim, Anders
core  

Differentiable Randers‐Finsler Eikonal Solvers

open access: yesComputer Graphics Forum, EarlyView.
Abstract Fast and differentiable solvers for anisotropic and asymmetric distance fields are a key primitive in geometry processing, enabling gradient‐based optimization over metrics, drift fields, and downstream objectives that depend on geodesic distances and geodesics.
Barak Gahtan   +2 more
wiley   +1 more source

Medial Axis Aware Learning of Signed Distance Functions

open access: yesComputer Graphics Forum, EarlyView.
Abstract We propose a novel variational method to compute a highly accurate global signed distance function (SDF) to a given point cloud. To this end, the jump set of the gradient of the SDF, which coincides with the medial axis of the surface, is explicitly taken into account through a higher‐order variational formulation that enforces linear growth ...
Samuel Weidemaier   +2 more
wiley   +1 more source

The Evolution of Interest‐Rate Models: From the Yield Curve to the Swaption Cube

open access: yesJournal of Economic Surveys, EarlyView.
ABSTRACT Interest‐rate modelling is often taught as a catalogue of competing stochastic equations, obscuring why models were created and why modern sell‐side desks use several simultaneously. This survey reorganises the field around five layers of a pricing architecture: curve construction; arbitrage‐free dynamics; volatility‐smile representation ...
Xuan Feng   +2 more
wiley   +1 more source

Measure‐valued processes for energy markets

open access: yesMathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.
Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero   +3 more
wiley   +1 more source

Reinforcement Learning for Jump‐Diffusions, With Financial Applications

open access: yesMathematical Finance, EarlyView.
ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley   +1 more source

Equilibrium Reward for Liquidity Providers in Automated Market Makers

open access: yesMathematical Finance, EarlyView.
ABSTRACT We find the equilibrium contract that an automated market maker (AMM) offers to their strategic liquidity providers (LPs) in order to maximize the order flow that gets processed by the venue. Our model is formulated as a leader–follower stochastic game, where the venue is the leader and a representative LP is the follower.
Alif Aqsha   +2 more
wiley   +1 more source

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