Results 81 to 90 of about 91,586,058 (209)

Controllable Intrinsic Surface Pattern Generation Using Slime Mold Simulations

Computer Graphics Forum, EarlyView.
Abstract Surface‐based pattern simulations have proven valuable for texture design and scientific visualization, but existing methods face several limitations. Most simulations either target a narrow range of pattern types (e.g. spots, branching) or support a broad range of patterns at the cost of time‐consuming parameter tuning.
Jeffrey Layton, Faramarz Samavati, Adam Runions   +2 more
wiley   +1 more source

Interpolated Adaptive Linear Reduced Order Modeling for Deformation Dynamics

Computer Graphics Forum, EarlyView.
Abstract Linear reduced‐order modeling (ROM) is widely used for efficient simulation of deformation dynamics, but its accuracy is often limited by the fixed linearization of the reduced mapping. We propose a new adaptive strategy for linear ROM that allows the reduced mapping to vary dynamically in response to the evolving deformation state ...
Y. Tao, M. Chiaramonte, P. Fernandez
wiley   +1 more source

Variational Approach to the Thomas-Fermi Equation

, 2003
By the semi-inverse method, a variational principle is obtained for the Thomas-Fermi equation, then the Ritz method is applied to solve an analytical solution, which is a much simpler and more efficient ...
何吉欢, He, JH (reprint author), Chinese Acad Sci, Inst Appl Math & Mech, Inst Mech, LNM, 149 Yanchang Rd, Shanghai 200072, Peoples R China.   +1 more
core   +1 more source

Comparison theorems for elliptic and parabolic operators in variational form [PDF]

, 2020
Dissertation (MSc (Applied Mathematics))--University of Pretoria, 2020.Order properties are normally derived from maximum principles associated with an operator, say $P$, in classical formulation. This result is often formulated as a comparison theorem

core  

Differentiable Randers‐Finsler Eikonal Solvers

Computer 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, Jacob Shpund, Alex M. Bronstein   +2 more
wiley   +1 more source

Circles of Confidence for Multi‐Label Geometry Completion

Computer Graphics Forum, EarlyView.
Abstract Inside–outside classification is widely used for geometry processing tasks such as surface reconstruction, geometry completion, and calculating signed distance fields. We introduce a new integral formulation of this problem, which assigns confidence scores that points are inside or outside, given incomplete boundary geometry.
Z. Wei, C. Hafner, A. Kalinov, P. Heiss‐Synak, C. Wojtan   +4 more
wiley   +1 more source

Medial Axis Aware Learning of Signed Distance Functions

Computer 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, Christoph Norden‐Smoch, Martin Rumpf   +2 more
wiley   +1 more source

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

Journal 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, Salman Huseynov, Diomides Mavroyiannis   +2 more
wiley   +1 more source

Measure‐valued processes for energy markets

Mathematical 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, Luca Di Persio, Francesco Guida, Sara Svaluto‐Ferro   +3 more
wiley   +1 more source

Reinforcement Learning for Jump‐Diffusions, With Financial Applications

Mathematical 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