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In this paper, we study the performance of a large family of SGD variants in the smooth nonconvex regime. To this end, we propose a generic and flexible assumption capable of accurate modeling of the second moment of the stochastic…

Optimization and Control · Mathematics 2020-06-15 Zhize Li , Peter Richtárik

The behavior of IAD_0 scheme, a fully conservative SPH scheme based on a tensor formulation, is analyzed in connection with several astrophysical scenarios, and compared to the same simulations carried out with the standard SPH technique.…

Instrumentation and Methods for Astrophysics · Physics 2015-06-05 Ruben M. Cabezon , Domingo Garcia-Senz , Jose Antonio Escartin

In this work, the exact reproduction of a moving-water steady flow via the numerical solution of the one-dimensional shallow water equations is studied. A new scheme based on a modified version of the HLLEM approximate Riemann solver…

Fluid Dynamics · Physics 2019-12-11 Valerio Caleffi , Alessandro Valiani

We develop an Explicitly Solvable Energy-Conserving (ESEC) algorithm for the Stochastic Differential Equation (SDE) describing the pitch-angle scattering process in magnetized plasmas. The Cayley transform is used to calculate both the…

Plasma Physics · Physics 2021-10-13 Yichen Fu , Xin Zhang , Hong Qin

Stochastic Partial Differential Equations (SPDEs) driven by random noise play a central role in modeling physical processes with rough spatio-temporal dynamics, such as turbulence flows, superconductors, and quantum dynamics. Although…

Machine Learning · Computer Science 2026-05-18 Yuantu Zhu , Zheyan Li , Dai Shi , Luke Thompson , Oliver Nash , Jose Miguel Lara Rangel , Siran Li , Bingguang Chen , Rongchan Zhu , Qi Meng , Hao Ni

The upwind conservation element and solution element (CESE) scheme is an alternative discontinuity-capturing numerical approach to solving hyperbolic conservation laws. To evaluate the numerical properties of this spatiotemporal coupled…

Fluid Dynamics · Physics 2024-10-31 Yazhong Jiang , Lisong Shi , Chih-Yung Wen

Making predictions and quantifying their uncertainty when the input data is sequential is a fundamental learning challenge, recently attracting increasing attention. We develop SigGPDE, a new scalable sparse variational inference framework…

Machine Learning · Statistics 2021-10-13 Maud Lemercier , Cristopher Salvi , Thomas Cass , Edwin V. Bonilla , Theodoros Damoulas , Terry Lyons

Learning dynamical systems is a promising avenue for scientific discoveries. However, capturing the governing dynamics in multiple environments still remains a challenge: model-based approaches rely on the fidelity of assumptions made for a…

Machine Learning · Computer Science 2023-03-09 MoonJeong Park , Youngbin Choi , Namhoon Lee , Dongwoo Kim

We present a framework for fine-tuning flow-matching generative models to enforce physical constraints and solve inverse problems in scientific systems. Starting from a model trained on low-fidelity or observational data, we apply a…

Machine Learning · Computer Science 2026-01-28 Jan Tauberschmidt , Sophie Fellenz , Sebastian J. Vollmer , Andrew B. Duncan

This work presents new parallelizable numerical schemes for the integration of Dissipative Particle Dynamics with Energy conservation (DPDE). So far, no numerical scheme introduced in the literature is able to correctly preserve the energy…

Computational Physics · Physics 2016-02-17 A. -A. Homman , J. -B. Maillet , J. Roussel , G. Stoltz

A robust nonconforming mixed finite element method is developed for a strain gradient elasticity (SGE) model. In two and three dimensional cases, a lower order $C^0$-continuous $H^2$-nonconforming finite element is constructed for the…

Numerical Analysis · Mathematics 2023-09-25 Mingqing Chen , Jianguo Huang , Xuehai Huang

Stochastic geometric mechanics (SGM) is known for its potential utility in quantifying uncertainty in global climate modelling of the Earth's ocean and atmosphere while also preserving the fundamental advective transport properties of ideal…

Fluid Dynamics · Physics 2023-08-30 Darryl D. Holm , Erwin Luesink

We consider the finite element (FE) approximation of the shallow water equations (SWE) by considering discretizations in which both space and time are established using an unconditionally stable FE method. Particularly, we consider the…

Numerical Analysis · Mathematics 2021-11-18 Eirik Valseth , Clint Dawson

We present a numerical formulation for the solution of non-isothermal, compressible, Navier-Stokes equations with thermal fluctuations to describe mesoscale transport phenomena in multispecies fluid mixtures. The novelty of our numerical…

This paper presents and analyzes two robust, efficient, and optimally accurate fully discrete finite element algorithms for computing the parameterized Navier-Stokes Equations (NSEs) flow ensemble. The timestepping algorithms are…

Numerical Analysis · Mathematics 2024-10-22 Neethu Suma Raveendran , Md Abdul Aziz , Muhammad Mohebujjaman

An energy stable finite element scheme within arbitrary Lagrangian Eulerian (ALE) framework is derived for simulating the dynamics of millimetric droplets in contact with solid surfaces. Supporting surfaces considered may exhibit…

Numerical Analysis · Mathematics 2022-01-11 Filip Ivančić , Maxim Solovchuk

Characterizing the long term behavior of dynamical systems given limited measurements is a common challenge throughout the physical and biological sciences. This is a challenging task due to the sparsity and noise inherent to empirical…

Machine Learning · Computer Science 2026-03-10 Roy Friedman , Noa Moriel , Matthew Ricci , Guy Pelc , Yair Weiss , Mor Nitzan

The Transformer architecture has revolutionized artificial intelligence, yet a principled theoretical understanding of its internal mechanisms remains elusive. This paper introduces a novel analytical framework that reconceptualizes the…

Machine Learning · Computer Science 2025-09-30 Yukun Zhang , Xueqing Zhou

A Skeleton-stabilized ImmersoGeometric Analysis technique is proposed for incompressible viscous flow problems with moderate Reynolds number. The proposed formulation fits within the framework of the finite cell method, where essential…

Accurate reconstruction of global Sea surface temperature (SST), which dominates the air-sea coupling and global climate variability, underpins climate monitoring and prediction. Existing SST reconstruction products primarily provide one…

Atmospheric and Oceanic Physics · Physics 2026-03-24 Haijie Li , Ya Wang , Kai Yang , Gang Huang , Xiangao Xia , Ziming Chen , Weichen Tao , Chenglin Lyu , Lin Chen , Miao Zhang , Kaiming Hu , Hainan Gong , Disong Fu , Lin Wang
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