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Infiltration under ponded conditions: 4. An explicit predictive infiltration formula

Publications associées (14)

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Biobased surfactant

Jeremy Luterbacher, Songlan Sun, Stefania Bertella, Anastasiia Komarova

The present invention relates to a compound of the general formula (I), (II) and (III), more specifically of formula (Ia), (Ib), (Ic)wherein R11 and R12 or R21 and R22 or R31 and R32 are both hydrogen or form together with CHR50 a cyclic moiety or one of R ...

2024

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The present invention relates to a cathepsin inhibitor comprising or consisting of Formula (I) (X1)(X2)(X3)(X4)(Y)(X5)(X6)(X7) wherein (X1) is an amino acid selected from K, L, F and M; (X2) is an amino acid selected from L, A, D, E, F, G, H, I, K, M, N, S ...

2023

Low-Rank Tensor Methods for High-Dimensional Problems

Christoph Max Strössner

In this thesis, we propose and analyze novel numerical algorithms for solving three different high-dimensional problems involving tensors. The commonality of these problems is that the tensors can potentially be well approximated in low-rank formats. Ident ...

EPFL2023

Product vacua with boundary states (PVBS) are cousins of the Heisenberg XXZ spin model and feature [Formula: see text] particle species on [Formula: see text]. The PVBS models were originally introduced as toy models for the classification of ground state ...

2019

A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming

Volkan Cevher, Alp Yurtsever

We propose a conditional gradient framework for a composite convex minimization template with broad applications. Our approach combines the notions of smoothing and homotopy under the CGM framework, and provably achieves the optimal O(1/sqrt(k)) convergenc ...

ICML2018

We analyze the recent Multi-index Stochastic Collocation (MISC) method for computing statistics of the solution of a partial differential equation (PDE) with random data, where the random coefficient is parametrized by means of a countable sequence of term ...

2016

Error Analysis of the Dynamically Orthogonal Approximation of Time Dependent Random PDEs

Fabio Nobile, Eleonora Musharbash

In this work we discuss the dynamically orthogonal (DO) approximation of time dependent partial differential equations with random data. The approximate solution is expanded at each time instant on a time dependent orthonormal basis in the physical domain ...

2015

We analyze the recent Multi-index Stochastic Collocation (MISC) method for computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a countable sequence of terms in a ...

MATHICSE2015

Small relative perturbations to the entries of an essentially nonnegative matrix introduce small relative errors to entries of its exponential. It is thus desirable to compute the exponential with high componentwise relative accuracy. Taylor series approxi ...

Siam Publications2014

Analysis of time compression approximations

David Andrew Barry, Marc Parlange

TCA, time compression approximation, is a practical and often quite accurate tool to predict postponding infiltration for field applications. A modified approximation (MTCA) can be used just as easily and, in general, will reduce the error by about 50%. Th ...

American Geophysical Union2011