Results 81 to 90 of about 856 (206)
SDFs from Unoriented Point Clouds using Neural Variational Heat Distances
Computer 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
Adaptive Finite Element Methods for Variational Inequalities: Theory and Applications in Finance [PDF]
, 2007 We consider variational inequalities (VIs) in a bounded open domain Omega subset IR^d with a piecewise smooth obstacle constraint. To solve VIs, we formulate a fully-discrete adaptive algorithm by using the backward Euler method for time discretization ...
Chen-song Zhang, Zhang, Chensong
core
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 +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
Enhancing CRISPR‐Cas12a base editing in plants with LbCas12a variants and introns
Journal of Integrative Plant Biology, EarlyView.Intron optimization of LbCas12a‐RRV improves cytosine and adenine base editing efficiency in plants, supports multiplexed and double‐strand break‐free genome modification, and expands precise genome engineering tools for crop breeding and plant functional research. ABSTRACT Cytosine base editors (CBEs) and adenine base editors (ABEs) are powerful tools
Yanhao Cheng +5 more
wiley +1 more source
Optimal energy growth lower bounds for a class of solutions to the vectorial Allen-Cahn equation
, 2014 We prove optimal lower bounds for the growth of the energy over balls of minimizers to the vectorial Allen-Cahn energy in two spatial dimensions, as the radius tends to infinity. In the case of radially symmetric solutions, we can prove a stronger result
Sourdis, Christos
core
One approach for describing spatio-temporally chaotic dynamical systems, including fluid turbulence, is to study non-chaotic but unstable invariant solutions embedded within the chaotic attractor of the system.
Ashtari, Omid
core +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 +3 more
wiley +1 more source
Geometric Integrators for Hamiltonian PDEs
, 2002 We consider methods for systematic construction of algorithms for a class of time-dependent PDEs with Hamiltonian structure. These systems possess phase space geometry and constants of the motion that need to be preserved by the integration algorithm to ...
Karpeev, Dmitry
core +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