Results 21 to 30 of about 58 (58)
Origin and application of the Lorentz factor in X‐ray diffraction
This review treats the role of the Lorentz factor in quantitative analysis of X‐ray diffraction data. The origin of the Lorentz factor, its derivation and practical implementations for a variety of modern X‐ray diffraction methods are discussed.The Lorentz factor is a fundamental correction factor in quantitative analysis of X‐ray diffraction ...
Fabian Gasser +5 more
wiley +1 more source
Abstract We estimate the price impact of very nearby concurrently listed properties in the Sydney housing market and assess their competition effects. We apply a hedonic model with spatiotemporal effects regularized via a graph Laplacian prior at the month‐by‐SA2 regional level to seven SA4 subregions of metropolitan Sydney. The model structure enables
Willem P. Sijp, Mengheng Li
wiley +1 more source
Neural Local Inter‐reflection Modeling for Garment Fold Rendering
Abstract Realistic garment rendering requires simulating complex multi‐bounce light paths within intricate fold geometries. In these regions, conventional path tracing is computationally expensive as light becomes trapped, necessitating high bounce counts for convergence.
Jooeun Son +4 more
wiley +1 more source
Progressively Projected Newton's Method
Abstract Newton's Method is widely used to find the solution of complex non‐linear simulation problems. To guarantee a descent direction, it is common practice to clamp the negative eigenvalues of each element Hessian prior to assembly—a strategy known as Projected Newton (PN)—but this perturbation often hinders convergence.
J. A. Fernández‐Fernández +2 more
wiley +1 more source
Hierarchical Optimization of the As‐Rigid‐As‐Possible Energy
Abstract The As‐Rigid‐As‐Possible (ARAP) energy [SA07] has become a versatile ingredient in various geometry processing and machine learning methods. The classic method for its minimization is a block coordinate descent, alternating between local rotation estimation and a global linear solve, which converges slowly for large problem instances.
Hendrik Meyer, Bernd Bickel, Marc Alexa
wiley +1 more source
Scalable Computation of Topological Abstractions for Scalar Data
Abstract Topological data analysis has become an important tool for large scale scalar data analysis and visualization, efficiently extracting the inherent structure and features of interest of the data. However, with growing dataset sizes and complexity, it is increasingly becoming infeasible to compute topological abstractions of interest in serial ...
M. Will +6 more
wiley +1 more source
Survey on Visualization of Information Diffusion over Networks
Abstract Information Diffusion (ID) describes how a value (e.g., a pathogen, a rumor, a packet) spreads through an underlying “medium” network of elements (e.g., a social or computer network). Understanding the information diffusion process is essential to predicting trends, controlling misinformation, and enhancing decision‐making as well as ...
T. Baumgartl +8 more
wiley +1 more source
Phong‐Rodrigues Extrinsic Vector‐Field Processing
Abstract We introduce a new extrinsic discretization of tangent vector fields on triangle meshes that is continuous, with bounded derivatives that are continuous almost everywhere, supporting pointwise evaluation and integration of differential operators.
Hongyi Liu +4 more
wiley +1 more source
Progressive Convex Hull Simplification
Abstract Convex hulls are useful as tight bounding proxies for a variety of tasks including collision detection, ray intersection, and distance computation. Unfortunately, the complexity of polyhedral convex hulls grows linearly with their input. We consider the problem of conservatively simplifying a convex hull to a specified number of half‐spaces ...
Alec Jacobson
wiley +1 more source
On Bending in the As‐Rigid‐As‐Possible Deformation Energy
Abstract The well‐established As‐Rigid‐As‐Possible (ARAP) energy has various forms. For surface deformation, commonly used energies contain an implicit bending penalty. We present a natural, continuous generalization that incorporates multiple ARAP versions with an implicit, user‐controllable bending penalty.
Ugo Finnendahl, Marc Alexa
wiley +1 more source

