Results 31 to 40 of about 84,089 (265)
Aerospace, 2023 This paper proposes an approach that combines manual differentiation (MD) and automatic differentiation (AD) to develop an efficient and accurate multi-row discrete adjoint solver.
Hangkong Wu +3 more
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CFD Analysis for Industrial Applications using xGrid Environment [PDF]
INCAS Bulletin, 2011 Relevant CFD computations are performed in a GRID environment in order to evaluate this technology as a reliable infrastructure for HPSC for complex industrial applications.
Catalin NAE
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TMB: Automatic Differentiation and Laplace Approximation
Journal of Statistical Software, 2016 TMB is an open source R package that enables quick implementation of complex nonlinear random effects (latent variable) models in a manner similar to the established AD Model Builder package (ADMB, http://admb-project.org/; Fournier et al. 2011).
Kasper Kristensen +4 more
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Journal of Marine Science and EngineeringThis paper is dedicated to the acoustic inversion of the vertical sound speed profiles (SSPs) in the underwater marine environment. The method of automatic differentiation is applied for the first time in this context.
Mikhail Lytaev
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Adjoints by automatic differentiation [PDF]
, 2014 AbstractThis chapter describes how adjoint algorithms can be created by automatic differentiation (AD). Data assimilation makes intensive use of gradients. In many situations, the so-called adjoint approach is generally the most efficient way to compute gradients, by propagating derivatives backwards from the result of the given model or function ...
openaire +2 more sources
Fully differentiable optimization protocols for non-equilibrium steady states
New Journal of Physics, 2021 In the case of quantum systems interacting with multiple environments, the time-evolution of the reduced density matrix is described by the Liouvillian.
Rodrigo A Vargas-Hernández +3 more
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Making Automatic Differentiation Truly Automatic: Coupling PETSc with ADIC [PDF]
Future Generation Computer Systems, 2002 Despite its name, automatic differentiation (AD) is often far from an automatic process. Often one must specify independent and dependent variables, indicate the derivative quantities to be computed, and perhaps even provide information about the structure of the Jacobians or Hessians being computed.
Hovland, P., Norris, B., Smith, B.
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A review of differentiable digital signal processing for music and speech synthesis
Frontiers in Signal ProcessingThe term “differentiable digital signal processing” describes a family of techniques in which loss function gradients are backpropagated through digital signal processors, facilitating their integration into neural networks.
Ben Hayes +4 more
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In situ molecular organization and heterogeneity of the Legionella Dot/Icm T4SS
FEBS Letters, EarlyView.We present a nearly complete in situ model of the Legionella Dot/Icm type IV secretion system, revealing its central secretion channel and identifying new components. Using cryo‐electron tomography with AI‐based modeling, our work highlights the structure, variability, and mechanism of this complex nanomachine, advancing understanding of bacterial ...
Przemysław Dutka +11 more
wiley +1 more source