Quadrature Based Neural Network Learning of Stochastic Hamiltonian Systems
Hamiltonian Neural Networks (HNNs) provide structure-preserving learning of Hamiltonian systems. In this paper, we extend HNNs to structure-preserving inversion of stochastic Hamiltonian systems (SHSs) from observational data.
Xupeng Cheng, Lijin Wang, Yanzhao Cao
doaj +1 more source
Model fit and parameter uncertainty in amortized variational inference based item response theory
Abstract Amortized variational inference (AVI) has become a popular, computationally efficient alternative to marginal maximum likelihood estimation (MML) for estimating high‐dimensional item response theory models on large datasets. However, currently the AVI framework lacks methods to assess model fit and determine parameter uncertainty.
K. Veldkamp +3 more
wiley +1 more source
SDFs from Unoriented Point Clouds using Neural Variational Heat Distances
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
Quadrature formulae of Euler-Maclaurin type based on generalized Euler polynomials of level m
This article deals with some properties -which are, to the best of our knowledge, new- of the generalized Euler polynomials of level $m$. These properties include a new recurrence relation satisfied by these polynomials and quadrature formulae of Euler ...
Yamilet Quintana, Alejandro Urieles
doaj
NEW DOCTORAL DEGREE Montgomery identity, quadrature formulae and derived inequalities [PDF]
The aim of this PhD dissertation is to give generalizations of classical quadrature formulae with two, three and four nodes using some generalizations of the weighted Montgomery identity.
Ribičić- Penava, Mihaela
core +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
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
Modelling tsunami initial conditions due to rapid coseismic seafloor displacement: efficient numerical integration and a tool to build unit source databases [PDF]
The initial conditions for the simulation of a seismically induced tsunami for a rapid, assumed-to-be-instantaneous vertical seafloor displacement is given by the Kajiura low-pass filter integral.
A. Abbate +7 more
doaj +1 more source
Appraisal of Six Natural Mica Reference Materials for In Situ Rb‐Sr Geochronology
Key Points Evaluated six natural mica reference materials for in situ LA‐ICP‐MS/MS Rb‐Sr geochronology using geochemical, microstructural and isotopic characterisation. Identified robust primary reference materials: Mount Dromedary biotite (99.37 Ma) and Mica‐Fe biotite (307.75 Ma). La Posta biotite and Högsbo muscovite are suitable secondary reference
Hugo K.H. Olierook +38 more
wiley +1 more source
In numerical analysis, the Boole’s formula serves as a pivotal tool for approximating definite integrals. The approximation of the definite integrals has a big role in numerical methods for differential equations; in particular, in the finite volume ...
Talha Anwar +4 more
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