Results 131 to 140 of about 97,059 (278)
Propellants, Explosives, Pyrotechnics, EarlyView.Physics‐Aware Recurrent Convolutional Neural Networks (PARC) can reliably learn the thermomechanics of energetic materials as a function of morphology. This work introduces LatentPARC, which accelerates PARC by modeling the dynamics in a low‐dimensional latent space.
Zoë J. Gray +5 more
wiley +1 more source
A structurally localized ensemble Kalman filtering approach
Quarterly Journal of the Royal Meteorological Society, EarlyView.We derive an inherently localized ensemble Kalman filtering (EnKF) approach, avoiding the need for any auxiliary localization technique. The idea is to first use the variational Bayesian optimization to approximate the (continuous) state analysis probability density function (pdf) by a product of independent marginal pdfs corresponding to small ...
Boujemaa Ait‐El‐Fquih +1 more
wiley +1 more source
p-Frame Multiresolution Analysis Related to the Walsh Functions
International Journal of Analysis and Applications, 2015 A generalization of the notion of p-multiresoltion analysis on a half-line, based on the theory of shift-invariant spaces is considered. In contrast to the standard setting, the associated subspace V0 of L2 (R+) has a frame, a collection of translates of
F.A. Shah
doaj +2 more sources
Invariant Subspaces with Invariant Complements [PDF]
Proceedings of the American Mathematical Society, 1969 openaire +2 more sources
Hybrid physics–data‐driven modeling for sea ice thermodynamics and transfer learning
Quarterly Journal of the Royal Meteorological Society, EarlyView.Icepack–NN, a machine‐learning‐based hybrid version of the sea‐ice column model Icepack, is developed to correct state‐dependent forecast errors arising from misspecified snow thermodynamics, using neural networks applied online within the physical model.
G. De Cillis +7 more
wiley +1 more source
Quality and Reliability Engineering International, EarlyView.ABSTRACT Upon establishing multiple response optimization (MRO) or dual response optimization (DRO), response surface methodology (RSM) acts as a conventional model‐driven framework for optimizing small‐sized experimental data to derive an input condition in which a decent response is expected.
Dong‐Hyun Koo +2 more
wiley +1 more source
Structural Concrete, EarlyView.Abstract This paper presents a numerical and experimental study aimed at the modeling and dynamic characterization of the reinforced concrete structure of the Palazzetto dello Sport in Rome, designed and by Pier Luigi Nervi with Annibale Vitellozzi, and built by Nervi & Bartoli contractors in 1956‐57.
Jacopo Ciambella +2 more
wiley +1 more source
Journal of High Energy PhysicsWe formulate a general fusion procedure for open $$\mathfrak{g}\mathfrak{l}(N)$$ spin chains. We construct the fused boundary reflection matrices and the corresponding fused reflection equations.
Nan Bai
doaj +1 more source
Boosted unsupervised feature selection for tumor gene expression profiles
CAAI Transactions on Intelligence Technology, EarlyView.Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi +5 more
wiley +1 more source
Vertical Deformation Mapping: Steering Optimiser Toward Flat Minima
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Standard deep learning optimisation is typically conducted on shape‐fixed loss surfaces. However, shape‐fixed loss surfaces may impede optimisers from reaching flat regions closely associated with strong generalisation. In this work, we propose a new paradigm named deformation mapping to deform the loss surface during optimisation.
Liangming Chen +4 more
wiley +1 more source