Wetland productivity and stability increase more with average plant size than with plant functional diversity. [PDF]
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Treatment-resistant recurrent unipolar and bipolar depression: associative learning abnormalities. [PDF]
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Prenatal paracetamol exposure and wheezing in infancy: a targeted maximum likelihood estimation application. [PDF]
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New anisotropic a priori error estimates
Numerische Mathematik, 2001We prove a priori anisotropic estimates for the $L^2$ and $H^1$ interpolation error on linear finite elements. The full information about the mapping from a reference element is employed to separate the contribution to the elemental error coming from different directions. This new
FORMAGGIA, LUCA, PEROTTO, SIMONA
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A Priori Inverse Operator Estimation for Guaranteed Error Estimate
Proceedings of the 4th International Workshop on Reliable Engineering Computing Robust Design – Coping with Hazards, Risk and Uncertainty – REC 2010, 2010A guaranteed error estimate procedure for linear or nonlinear two-point boundary value problems is established by authors. ‘Guaranteed’ error estimate is rigorous, i.e. it takes into account every error such as the discretization error and the rounding error when we compute an approximate solution.
Kubo T., Oishi S., Takayasu A.
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New A Priori FEM Error Estimates for Eigenvalues
SIAM Journal on Numerical Analysis, 2006We analyze the Ritz--Galerkin method for symmetric eigenvalue problems and prove a priori eigenvalue error estimates. For a simple eigenvalue, we prove an error estimate that depends mainly on the approximability of the corresponding eigenfunction and provide explicit values for all constants.
Andrew V. Knyazev, John E. Osborn
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A Priori Estimates of the Generalization Error for Autoencoders
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020Autoencoder is a machine learning model which aims for dimensionality reduction, by reconstructing its input through a bottleneck with lower dimension than the input. It is among the most popular models used in unsupervised learning and semi-supervised learning. In this paper, we build theoretical understanding about autoencoders.
Zehao Don, Weinan E., Chao Ma
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Unified a Priori Error Estimate and a Posteriori Error Estimate of CIP-FEM for Elliptic Equations
Advances in Applied Mathematics and Mechanics, 2016AbstractThis paper is devoted to a unified a priori and a posteriori error analysis of CIP-FEM (continuous interior penalty finite element method) for second-order elliptic problems. Compared with the classic a priori error analysis in literature, our technique can easily apply for any type regularity assumption on the exact solution, especially for ...
Wang, Jianye, Ma, Rui
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On a priori error estimates of some identification methods
IEEE Transactions on Automatic Control, 1970This paper examines in detail the estimation errors of two algorithms proposed by Koopmans [1] and Levin [2] for identifying linear systems described by an n th-order scalar difference equation. Necessary and sufficient conditions are established for the strong consistency of the estimates that these algorithms generate.
M. Aoki, P. Yue
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Estimation of bit error probabilities using a priori information
Seamless Interconnection for Universal Services. Global Telecommunications Conference. GLOBECOM'99. (Cat. No.99CH37042), 2003The coded data stream of today's powerful source codecs still contains residual redundancy. Due to the fact that coding is usually done frame by frame, this redundancy remains both inside a frame and also in a time correlation of successive frames. The redundancy should be used as a priori information at the receiver to improve the decoding result ...
M. Kaindl, T. Hindelang
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