Results 21 to 30 of about 87,618 (263)
Selective Path Automatic Differentiation: Beyond Uniform Distribution on Backpropagation Dropout
IEEE Access, 2023 This paper introduces Selective Path Automatic Differentiation (SPAD), a novel approach to reducing memory consumption and mitigating overfitting in gradient-based models for embedded artificial intelligence.
Paul Peseux +3 more
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Differentiable Automatic Data Augmentation [PDF]
, 2020 Data augmentation (DA) techniques aim to increase data variability, and thus train deep networks with better generalisation. The pioneering AutoAugment automated the search for optimal DA policies with reinforcement learning. However, AutoAugment is extremely computationally expensive, limiting its wide applicability.
Li, Yonggang +5 more
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Evolution of perturbations in 3D air quality models
Annals of Geophysics, 2003 The deterministic approach of sensitivity analysis is applied on the solution vector of an Air Quality Model. In particular, the photochemical CAMx code is augmented with derivatives utilising the automatic differentiation software ADIFOR.
I. Ziomas +3 more
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ACORNS: An easy-to-use code generator for gradients and Hessians
SoftwareX, 2022 The computation of first and second-order derivatives is a staple in many computing applications, ranging from machine learning to scientific computing. We propose an algorithm to automatically differentiate algorithms written in a subset of C99 code and
Deshana Desai +4 more
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The New Approach to Analysis of Thin Isotropic Symmetrical Plates
Applied Sciences, 2020 A new approach to solve plate constructions using combined analytical and numerical methods has been developed in this paper. It is based on an exact solution of an equilibrium equation.
Mykhaylo Delyavskyy, Krystian Rosiński
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A Hitchhiker’s Guide to Automatic Differentiation [PDF]
Numerical Algorithms, 2015 39 pages, 10 figures, Numerical Algorithms (2015)
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Symbolic and automatic differentiation of languages [PDF]
Proceedings of the ACM on Programming Languages, 2021 Formal languages are usually defined in terms of set theory. Choosing type theory instead gives us languages as type-level predicates over strings. Applying a language to a string yields a type whose elements are language membership proofs describing how a string parses in the language.
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Optimization of a Micromixer with Automatic Differentiation
Fluids, 2022 As micromixers offer the cheap and simple mixing of fluids and suspensions, they have become a key device in microfluidics. Their mixing performance can be significantly increased by periodically varying the inlet pressure, which leads to a non-static ...
Julius Jeßberger +5 more
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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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