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This article introduces a new efficient particle method for the numerical simulation of crystallization and precipitation at the pore scale of real rock geometries extracted by X-Ray tomography. It is based on the coupling between…

Computational Engineering, Finance, and Science · Computer Science 2025-03-11 Sarah Perez , Jean-Matthieu Etancelin , Philippe Poncet

Gradient clipping is commonly used in training deep neural networks partly due to its practicability in relieving the exploding gradient problem. Recently, \citet{zhang2019gradient} show that clipped (stochastic) Gradient Descent (GD)…

Machine Learning · Computer Science 2020-10-30 Bohang Zhang , Jikai Jin , Cong Fang , Liwei Wang

Slender structures immersed in a cross flow can experience vibrations induced by vortex shedding (VIV), which cause fatigue damage and other problems. VIV models in engineering use today tend to operate in the frequency domain. A time…

Fluid Dynamics · Physics 2010-10-26 Philippe Maincon

The recent surge in earthquake engineering is the use of machine learning methods to develop predictive models for structural behavior. Complex black-box models are typically used for decision making to achieve high accuracy; however, as…

Geophysics · Physics 2022-05-19 Zeynep Tuna Deger , Gulsen Taskin Kaya

In this paper we develop random block coordinate gradient descent methods for minimizing large scale linearly constrained separable convex problems over networks. Since we have coupled constraints in the problem, we devise an algorithm that…

Optimization and Control · Mathematics 2015-12-14 I. Necoara , Yu. Nesterov , F. Glineur

Inverse problems have many applications in science and engineering. In Computer vision, several image restoration tasks such as inpainting, deblurring, and super-resolution can be formally modeled as inverse problems. Recently, methods have…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Sai Bharath Chandra Gutha , Ricardo Vinuesa , Hossein Azizpour

A novel damage localization method is proposed, which is based on a substructuring approach and makes use of Vector Auto-Regressive with eXogenous input (VARX) models. The substructuring approach aims to divide the monitored structure into…

Systems and Control · Computer Science 2015-01-09 U. Ugalde , J. Anduaga , F. Martinez , A. Iturrospe

In recent years, spectral clustering has become a standard method for data analysis used in a broad range of applications. In this paper we propose a new class of algorithms for multiway spectral clustering based on optimization of a…

Machine Learning · Computer Science 2016-05-05 James Voss , Mikhail Belkin , Luis Rademacher

We present in this paper a novel numerical reconstruction method for solving a 3D coefficient inverse problem with scattering data generated by a single direction of the incident plane wave. This inverse problem is well-known to be a highly…

Numerical Analysis · Mathematics 2018-05-22 Michael V. Klibanov , Aleksandr E. Kolesov , Dinh-Liem Nguyen

During an earthquake, slip occurs in a localised shear zone that features a heavily granulated fault core that can be characterised as a shear band. We study the formation of this fault core in a granular rock such as sandstone by…

Geophysics · Physics 2025-09-29 N. A. Collins-Craft , I. Stefanou , J. Sulem , I. Einav

The numerical simulation of physical processes in the underground frequently entails challenges related to the geometry and/or data. The former are mainly due to the shape of sedimentary layers and the presence of fractures and faults,…

Numerical Analysis · Mathematics 2020-02-28 Alessio Fumagalli , Anna Scotti , Luca Formaggia

Penetration models and calculating algorithms are presented, describing the dynamics and fracture of composite armor shields penetrated by high-speed small arms. A shield considered consists of hard (metal or ceramic) facing and…

Mathematical Physics · Physics 2012-03-08 Mark Ayzenberg-Stepanenko , Grigory Osharovich

Erasure-coded computing has been successfully used in cloud systems to reduce tail latency caused by factors such as straggling servers and heterogeneous traffic variations. A majority of cloud computing traffic now consists of inference on…

Machine Learning · Computer Science 2024-09-04 Divyansh Jhunjhunwala , Neharika Jali , Gauri Joshi , Shiqiang Wang

SUMMARY Geophysical imaging using the inversion procedure is a powerful tool for the exploration of the Earth's subsurface. However, the interpretation of inverted images can sometimes be difficult, due to the inherent limitations of…

Noise is one of the primary sources of interference in seismic exploration. Many authors have proposed various methods to remove noise from seismic data; however, in the face of strong noise conditions, satisfactory results are often not…

Geophysics · Physics 2024-04-04 Junheng Peng , Yong Li , Yingtian Liu , Zhangquan Liao

Recent focus on robustness to adversarial attacks for deep neural networks produced a large variety of algorithms for training robust models. Most of the effective algorithms involve solving the min-max optimization problem for training…

Machine Learning · Computer Science 2021-03-03 Yasaman Esfandiari , Aditya Balu , Keivan Ebrahimi , Umesh Vaidya , Nicola Elia , Soumik Sarkar

Sparse-view Computed Tomography (CT) is an emerging protocol designed to reduce X-ray dose radiation in medical imaging. Traditional Filtered Back Projection algorithm reconstructions suffer from severe artifacts due to sparse data. In…

Numerical Analysis · Mathematics 2024-12-03 Elena Loli Piccolomini , Davide Evangelista , Elena Morotti

We investigate a fundamental model from open-pit mining, which is a cyclic system consisting of a shovel, traveling loaded, unloading facility, and traveling back empty. The interaction of these subsystem determines the capacity of the…

Optimization and Control · Mathematics 2016-04-18 Hans Daduna , Ruslan Krenzler , Robert Ritter , Dietrich Stoyan

Global minimum cut is a fundamental combinatorial optimization problem with wide-ranging applications. Often in practice, these problems are solved repeatedly on families of similar or related instances. However, the de facto algorithmic…

Data Structures and Algorithms · Computer Science 2025-03-10 Benjamin Moseley , Helia Niaparast , Karan Singh

We explore why many recently proposed robust estimation problems are efficiently solvable, even though the underlying optimization problems are non-convex. We study the loss landscape of these robust estimation problems, and identify the…

Machine Learning · Statistics 2020-05-29 Banghua Zhu , Jiantao Jiao , Jacob Steinhardt