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Showing 27163 results for "xavier martorell"
Mathematics Preprint PDF DOI

Beyond first-order accuracy in continuous-forcing immersed boundary methods, and their well-conditioned projection-based solution

Diederik Beckers, H. Jane Bae, Andres Goza ยท 2026

We introduce a refined immersed boundary (IB) methodology that is better-than-first-order accurate in practice, while preserving key properties of "continuous-forcing" IB approaches that retain a singโ€ฆ

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Computer Science Preprint PDF DOI

Claw-Eval-Live: A Live Agent Benchmark for Evolving Real-World Workflows

Chenxin Li, Zhengyang Tang, Huangxin Lin, Yunlong Lin, Shijue Huang, Shengyuan Liu, Bowen Ye, Rang Li, Lei Li, Benyou Wang, Yixuan Yuan ยท 2026

LLM agents are expected to complete end-to-end units of work across software tools, business services, and local workspaces. Yet many agent benchmarks freeze a curated task set at release time and graโ€ฆ

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AI & Data Science Preprint PDF DOI

Exponential families from a single KL identity

Marc Dymetman ยท 2026

Exponential families encompass the distributions central to modern machine learning -- softmax, Gaussians, and Boltzmann distributions -- and underlie the theory of variational inference, entropy-reguโ€ฆ

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Physics Preprint PDF DOI

Mixture-aware closure of the N-phase Navier--Stokes--Cahn--Hilliard mixture model

M.F.P. ten Eikelder, A. Brunk ยท 2026

Diffuse-interface (phase-field) models are widely used to describe multiphase mixtures and their interfacial dynamics. In multiphase settings, however, the constitutive closure should remain meaningfuโ€ฆ

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Physics Preprint PDF DOI

Sampling two-dimensional spin systems with transformers

Piotr Bia{l}as, Piotr Korcyl, Tomasz Stebel, Adam Stefanski, Dawid Zapolski ยท 2026

Autoregressive Neural Networks based on dense or convolutional layers have recently been shown to be a viable strategy for generating classical spin systems. Unlike these methods, sampling with transfโ€ฆ

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Mathematics Preprint PDF DOI

A divisor function of Wigert and higher degree forms

Debika Banerjee, Atul Dixit, Rajat Gupta ยท 2026

Let $k\in\mathbb{N}$. Wigert's divisor function $d^{\left(\frac{1}{k}\right)}(j)$ counts the number of representations of $j$ of the form $m^k+mn$ with $m\geq1 , n\geq0$. Let $\mathcal{F}_k(s)$ denoteโ€ฆ

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Physics Preprint PDF DOI

Cahn-Hilliard Phase Field modelling captures nanoscale contact line dynamics on high-friction surfaces

Michele Pellegrino, Parvathy K. Kannan, Gustav Amberg, Shervin Bagheri, Outi Tammisola, Berk Hess ยท 2026

Incorporating molecular-scale effects in the description of contact line motion is essential for accurately capturing all sources of energy dissipation in wetting dynamics. This holds particularly truโ€ฆ

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Physics Preprint PDF DOI

To stall-cell or not to stall-cell: Variational data assimilation of 3D mean flow past a stalled airfoil

Uttam Cadambi Padmanaban, Craig Thompson, Bharathram Ganapathisubramani, Sean Symon ยท 2026

The full-field reconstruction of three-dimensional (3D) turbulent flows from sparse experimental measurements remains a significant challenge, particularly for flows exhibiting complex 3D flow separatโ€ฆ

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Mathematics Preprint PDF DOI

A Systematic Review of Recent Advancements in PINN Augmented Deep Learning and Mathematical Modeling for Efficient Portfolio Management

Bahadur Yadav, Sanjay Kumar Mohanty ยท 2026

In finance, portfolio management is a traditional yet difficult problem that has drawn attention from practitioners and researchers for many years. However, there are still difficult technological proโ€ฆ

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Mathematics Preprint PDF DOI

Discontinuous Galerkin IMEX Pressure Correction Scheme for the Poisson-Nernst-Planck-Navier-Stokes Equations

Bikram Bir, Amiya K. Pani ยท 2026

Based on a discontinuous Galerkin method in the spatial directions and an improved implicit-explicit pressure-correction scheme in the temporal direction, this paper discusses a fully discrete scheme โ€ฆ

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AI & Data Science Preprint PDF DOI

Detecting is Easy, Adapting is Hard: Local Expert Growth for Visual Model-Based Reinforcement Learning under Distribution Shift

Haiyang Zhao ยท 2026

Visual model-based reinforcement learning (MBRL) agents can perform well on the training distribution, but often break down once the test environment shifts. In visual MBRL, recognizing that a shift hโ€ฆ

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Physics Preprint PDF DOI

Compressible Navier--Stokes Flow in Schr\"odinger-Type Variables

James R. Beattie, Max Sokolova, Khush Negandhi, Bart Ripperda ยท 2026

Fluid equations are nonlinear, dissipative, and non-Hamiltonian, which makes their relation to Schr\"odinger evolution and quantum algorithms nontrivial. We derive an exact Eulerian Cole-Hopf-type refโ€ฆ

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Mathematics Preprint PDF DOI

Data assimilation for slightly compressible flow

Aytekin C{i}b{i}k, Rui Fang ยท 2026

Continuous data assimilation (CDA) nudges observational data into governing equations to recover the underlying flow and improve predictions. Existing rigorous CDA analyses focus primarily on incompreโ€ฆ

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Mathematics Preprint PDF DOI

Global weak solutions to a diffuse-interface model for quasi-incompressible two-phase flows with unmatched densities and singular potential

Mingwen Fei, Xiang Fei, Yadong Liu, Hao Wu ยท 2026

We study a thermodynamically consistent diffuse-interface model that describes the motion of two macroscopically immiscible, incompressible, and viscous Newtonian fluids with unmatched densities. Thisโ€ฆ

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Physics Preprint PDF DOI

A Hybrid Gas-Kinetic Scheme and Discrete Velocity Method for Continuum and Rarefied Flows

Hangkong Wu, Yuze Zhu, Yajun Zhu, Kun Xu ยท 2026

The gas-kinetic scheme (GKS) provides high computational efficiency and accuracy for continuum flow simulations but is unable to reliably capture rarefaction effects. In contrast, although the discretโ€ฆ

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Mathematics Preprint PDF DOI

Boundary epsilon regularity for incompressible Navier--Stokes equations via weak-strong uniqueness

Siran Li ยท 2026

We show that finite-energy weak solutions to the incompressible Navier--Stokes equations on a three-dimensional bounded smooth domain are regular up to the boundary, provided that the $L^4_tL^4_x$-norโ€ฆ

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AI & Data Science Preprint PDF DOI

Towards interpretable AI with quantum annealing feature selection

Francesco Aldo Venturelli, Emanuele Costa, Sikha O K, Bruno Julia-Diaz, Miguel A. Gonzalez Ballester, Alba Cervera-Lierta ยท 2026

Deep learning models are used in critical applications, in which mistakes can have serious consequences. Therefore, it is crucial to understand how and why models generate predictions. This understandโ€ฆ

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AI & Data Science Preprint PDF DOI

Sample-efficient Neuro-symbolic Proximal Policy Optimization

Simone Murari, Celeste Veronese, Daniele Meli ยท 2026

Deep Reinforcement Learning (DRL) algorithms often require a large amount of data and struggle in sparse-reward domains with long planning horizons and multiple sub-goals. In this paper, we propose a โ€ฆ

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Mathematics Preprint PDF DOI

Conditonal Lipschitz stability for the Inverse Problem of the 2D Navier-Stokes System in a Bounded Domain

Jishan Fan, Yu Jiang, Sei Nagayasu, Gen Nakamura ยท 2026

This paper concerns an inverse problem for the initial boundary value problem of the two-dimensional Navier-Stokes system defined in a bounded simply connected domain with slip, vorticity boundary conโ€ฆ

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AI & Data Science Preprint PDF DOI

DDA-Thinker: Decoupled Dual-Atomic Reinforcement Learning for Reasoning-Driven Image Editing

Hanqing Yang, Qiang Zhou, Yongchao Du, Sashuai Zhou, Zhibin Wang, Jun Song, Tiezheng Ge, Cheng Yu, Bo Zheng ยท 2026

Recent image editing models have achieved strong visual fidelity but often struggle with tasks requiring complex reasoning. To investigate and enhance the reasoning-grounded planning for image editingโ€ฆ

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