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We study counterfactual distribution learning for high-dimensional outcomes whose counterfactual law may concentrate near lower-dimensional structure. Standard isotropic smoothing treats all ambient directions equally, leading to…

Methodology · Statistics 2026-05-26 Kwangho Kim

In this work we propose an Uncertainty Quantification methodology for sedimentary basins evolution under mechanical and geochemical compaction processes, which we model as a coupled, time-dependent, non-linear, monodimensional (depth-only)…

Numerical Analysis · Mathematics 2017-11-22 Ivo Colombo , Fabio Nobile , Giovanni Porta , Anna Scotti , Lorenzo Tamellini

Many subsurface formations, including some of those under consideration for large-scale geological carbon storage, include extensive faults that can strongly impact fluid flow. In this study, we develop a new recurrent transformer U-Net…

Machine Learning · Computer Science 2025-08-26 Yifu Han , Louis J. Durlofsky

Surface analyses inside the nanopore, micropore, and a very narrow pipe are important topics for development of the chemical engineering. Here, we propose a measuring method which evaluates the surface coverage of the chemically modified…

Chemical Physics · Physics 2015-04-07 Ken-ichi Amano

Over the last few decades, phase-field equations have found increasing applicability in a wide range of mathematical-scientific fields (e.g. geometric PDEs and mean curvature flow, materials science for the study of phase transitions) but…

Pattern Formation and Solitons · Physics 2017-02-28 M. Schmuck , S. Kalliadasis

The problem of diffusion in a porous medium with a spatially varying porosity is considered. The particular microstructure analyzed comprises a collection of impenetrable spheres, though the methods developed are general. Two different…

Fluid Dynamics · Physics 2017-10-12 Maria Bruna , S. Jonathan Chapman

This work represents an application of constant mean curvature graphs (as solutions of the mean curvature PDE) to non-linear non-Darcy flows in porous media. It relates time invariant pressure distribution graphs to graphs of constant mean…

Differential Geometry · Mathematics 2013-02-26 Eugenio Aulisa , Akif Ibragimov , Magdalena Toda

In this paper, we develop a general framework for multicontinuum homogenization in perforated domains. The simulations of problems in perforated domains are expensive and, in many applications, coarse-grid macroscopic models are developed.…

Numerical Analysis · Mathematics 2024-04-29 Wei Xie , Yalchin Efendiev , Yunqing Huang , Wing Tat Leung , Yin Yang

A new OpenFOAM application to simulate multiphase flows in porous media is formulated and tested. The proposed solver combines the Eulerian multi-fluid formulation for a system of phase fractions with Darcy's law for flows through porous…

We have considered a semi-infinite crack embedded in a transversely isotropic medium and studied two special cases, one, in which the axis of symmetry is normal to the crack face and the wave incidence is arbitrary and another, in which the…

Mathematical Physics · Physics 2009-02-25 A. Gautesen , V. Zernov , L. Fradkin

There is a wide range of stabilized finite element methods for stationary and non-stationary convection-diffusion equations such as streamline diffusion methods, local projection schemes, subgrid-scale techniques, and continuous interior…

Numerical Analysis · Mathematics 2014-02-25 L. Tobiska , R. Verfürth

This article investigates the non-stationary reaction-diffusion-advection equation, emphasizing solutions with internal layers and the associated inverse problems. We examine a nonlinear singularly perturbed partial differential equation…

Numerical Analysis · Mathematics 2025-02-06 Dmitrii Chaikovskii , Ye Zhang , Aleksei Liubavin

The shrinking core model describes the reaction of a spherical solid particle with a surrounding fluid. In this work, we revisit the SCM by deriving it from the underlying physical processes and performing a careful non-dimensionalisation,…

Other Condensed Matter · Physics 2025-08-05 Cristian Moreno-Pulido , Rachael Olwande , Tim Myers , Francesc Font

In this paper, we present a dimension reduction method to reduce the dimension of parameter space and state space and efficiently solve inverse problems. To this end, proper orthogonal decomposition (POD) and radial basis function (RBF) are…

Numerical Analysis · Mathematics 2016-10-18 Fuchen Chen , Lijian Jiang , Guanghui Zheng

We derive a numerical method, based on operator splitting, to abstract parabolic semilinear boundary coupled systems. The method decouples the linear components which describe the coupling and the dynamics in the bulk and on the surface,…

Numerical Analysis · Mathematics 2022-10-19 Petra Csomós , Bálint Farkas , Balázs Kovács

The `renormalon' or `dispersive' method for estimating non-perturbative corrections to QCD observables is reviewed. The corrections are power-suppressed, i.e. of the form $A/Q^p$ where $Q$ is the hard process momentum scale. The renormalon…

High Energy Physics - Phenomenology · Physics 2009-10-30 B. R. Webber

We present a unified framework for solving partial differential equations (PDEs) using video-inpainting diffusion transformer models. Unlike existing methods that devise specialized strategies for either forward or inverse problems under…

Machine Learning · Computer Science 2025-06-18 Edward Li , Zichen Wang , Jiahe Huang , Jeong Joon Park

Recently, diffusion models have been used to solve various inverse problems in an unsupervised manner with appropriate modifications to the sampling process. However, the current solvers, which recursively apply a reverse diffusion step…

Machine Learning · Computer Science 2024-05-21 Hyungjin Chung , Byeongsu Sim , Dohoon Ryu , Jong Chul Ye

Liquid dropout and retention in gas-condensate reservoirs, specially in the near wellbore region, obstruct gas flowing paths and impact negatively the produced fluid volume and composition. Yet, condensate banking forecasting is commonly…

Fluid Dynamics · Physics 2020-11-18 Paula Reis , Marcio Carvalho

Conditional diffusion probabilistic models can model the distribution of natural images and can generate diverse and realistic samples based on given conditions. However, oftentimes their results can be unrealistic with observable color…

Computer Vision and Pattern Recognition · Computer Science 2022-12-15 Kangfu Mei , Nithin Gopalakrishnan Nair , Vishal M. Patel