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Transformer layers, which use an alternating pattern of multi-head attention and multi-layer perceptron (MLP) layers, provide an effective tool for a variety of machine learning problems. As the transformer layers use residual connections…

Machine Learning · Computer Science 2022-12-13 Yaofeng Desmond Zhong , Tongtao Zhang , Amit Chakraborty , Biswadip Dey

Surrogate modeling is a viable solution for applications involving repetitive evaluations of expensive computational fluid dynamics models, such as uncertainty quantification and inverse problems. This study proposes a multi-layer…

Fluid Dynamics · Physics 2024-06-24 Gurpreet S. Hora , Marco G. Giometto

As large language models (LLMs) continue to scale up, mixture-of-experts (MoE) has become a common technology in SOTA models. MoE models rely on expert parallelism (EP) to alleviate memory bottleneck, which introduces all-to-all…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-30 Xinru Tang , Jingxiang Hou , Dingcheng Jiang , Taiquan Wei , Jiaxin Liu , Jinyi Deng , Huizheng Wang , Qize Yang , Haoran Shang , Chao Li , Yang Hu , Shouyi Yin

Where performance comparison of healthcare providers is of interest, characteristics of both patients and the health condition of interest must be balanced across providers for a fair comparison. This is unlikely to be feasible within…

Methodology · Statistics 2019-09-04 Wendy J. Harrison , Paul D. Baxter , Mark S. Gilthorpe

We study turbulent flows in planar channels with unstable thermal stratification, using direct numerical simulations in a wide range of Reynolds and Rayleigh numbers and reaching flow conditions which are representative of asymptotic…

Fluid Dynamics · Physics 2017-06-28 Sergio Pirozzoli , Matteo Bernardini , Roberto Verzicco , Paolo Orlandi

Much work has been done on relaxation oscillations and other simple oscillators in conceptual climate models. However, the oscillatory patterns in climate data are often more complicated than what can be described by such mechanisms. This…

Dynamical Systems · Mathematics 2014-12-02 Andrew Roberts , Esther Widiasih , Chris K. R. T. Jones , Martin Wechselberger

As foundational models reshape scientific discovery, a bottleneck persists in dynamical system reconstruction (DSR): the ability to learn across system hierarchies. Many meta-learning approaches have been applied successfully to single…

Machine Learning · Computer Science 2025-06-12 Roussel Desmond Nzoyem , Grant Stevens , Amarpal Sahota , David A. W. Barton , Tom Deakin

We propose a multi-layer approach to simulate hyperpycnal and hypopycnal plumes in flows with free surface. The model allows to compute the vertical profile of the horizontal and the vertical components of the velocity of the fluid flow.…

Fluid Dynamics · Physics 2017-05-16 T. Morales de Luna , E. D. Fernández-Nieto , M. J. Castro Díaz

We propose a Bayesian model for mixed ordinal and continuous multivariate data to evaluate a latent spatial Gaussian process. Our proposed model can be used in many contexts where mixed continuous and discrete multivariate responses are…

Methodology · Statistics 2013-05-22 Erin M. Schliep , Jennifer A. Hoeting

This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing…

Fluid Dynamics · Physics 2024-05-31 Matteo Zancanaro , Valentin Nkana Ngan , Giovanni Stabile , Gianluigi Rozza

Flow-level simulation is widely used to model large-scale data center networks due to its scalability. Unlike packet-level simulators that model individual packets, flow-level simulators abstract traffic as continuous flows with dynamically…

Networking and Internet Architecture · Computer Science 2025-03-04 Chenning Li , Anton A. Zabreyko , Arash Nasr-Esfahany , Kevin Zhao , Prateesh Goyal , Mohammad Alizadeh , Thomas Anderson

We generalize the multilevel Monte Carlo (MLMC) method of Giles to the simulation of systems of particles that interact via a mean field. When the number of particles is large, these systems are described by a McKean-Vlasov process - a…

Numerical Analysis · Mathematics 2015-08-11 L. F. Ricketson

Experimental results for passive tracer dispersion in the turbulent surface layer under convective conditions are presented. In this case, the dispersion of tracer particles is determined by the interplay of two mechanisms: buoyancy and…

Chaotic Dynamics · Physics 2014-08-26 Alex Skvortsov , Milan Jamriska , Timothy C DuBois

The water following characteristics of six different drifter types are investigated using two different operational marine environmental prediction systems: one produced by Environment and Climate Change Canada (ECCC) and the other produced…

In this study, the ducted propeller has been numerically investigated under oblique flow, which is crucial and challenging for the design and safe operation of thruster driven vessel and dynamic positioning (DP) system. A Reynolds-Averaged…

Fluid Dynamics · Physics 2018-01-11 Qin Zhang , Rajeev K. Jaiman , Peifeng Ma , Jing Liu

A mean-field model to describe electron transfer processes in ion-molecule collisions at the $\hbar =0$ level is presented and applied to collisions involving water and ammonia molecules. Multicenter model potentials account for the…

Atomic Physics · Physics 2023-11-21 Alba Jorge , Marko Horbatsch , Tom Kirchner

Breaching of earthen or sandy dams/dunes by overtopping flow and waves is a complicated process with strong, unsteady flow, high sediment transport, and rapid bed changes in which the interactions between flow and morphology should not be…

Fluid Dynamics · Physics 2015-08-06 Zhiguo He , Peng Hu , Liang Zhao , Ganfeng Wu , Thomas Pähtz

We conducted WMLES to examine the performance of a simple and widely used ODE-based equilibrium wall model in a spatially-developing 3D TBL inside a bent square duct (Schwarz and Bradshaw 1994) and 3D separated flows behind a skewed bump…

Fluid Dynamics · Physics 2020-01-07 Minjeong Cho , George I. Park , Adrián Lozano-Durán , Parviz Moin

This paper studies the fundamental problem of learning multi-layer generator models. The multi-layer generator model builds multiple layers of latent variables as a prior model on top of the generator, which benefits learning complex data…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Jiali Cui , Ying Nian Wu , Tian Han
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