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Recent progress in compressing explicit radiance field representations, particularly 3D Gaussian Splatting, has substantially reduced memory consumption while improving real-time rendering performance. However, existing approaches remain…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Francesco Di Sario , Riccardo Renzulli , Marco Grangetto , Akihiro Sugimoto , Enzo Tartaglione

Despite a large corpus of recent work on scaling up Gaussian processes, a stubborn trade-off between computational speed, prediction and uncertainty quantification accuracy, and customizability persists. This is because the vast majority of…

Machine Learning · Computer Science 2025-12-09 Marcus M. Noack , Mark D. Risser , Hengrui Luo , Vardaan Tekriwal , Ronald J. Pandolfi

Using a Maximum Entropy Production Principle (MEPP), we derive a new type of relaxation equations for two-dimensional turbulent flows in the case where a prior vorticity distribution is prescribed instead of the Casimir constraints [Ellis,…

Fluid Dynamics · Physics 2015-03-13 P. H. Chavanis , A. Naso , B. Dubrulle

This paper presents an extension of the hybrid scheme proposed by Wang et al. (J. Comput. Phys. 229 (2010) 169-180) for numerical simulation of compressible isotropic turbulence to flows with higher turbulent Mach numbers. The scheme still…

Computational Physics · Physics 2021-03-11 L. Q. Liu , J. C. Wang , Y. P. Shi , S. Y. Chen , X. T. He

Implicit Neural Representation for Videos (NeRV) has introduced a novel paradigm for video representation and compression, outperforming traditional codecs. As model size grows, however, slow encoding and decoding speed and high memory…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Inseo Lee , Youngyoon Choi , Joonseok Lee

We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated on a patient-specific stenosed aorta. The framework…

We propose a method that achieves state-of-the-art rendering quality and efficiency on monocular dynamic scene reconstruction using deformable 3D Gaussians. Implicit deformable representations commonly model motion with a canonical space…

Computer Vision and Pattern Recognition · Computer Science 2025-01-17 Yiqing Liang , Numair Khan , Zhengqin Li , Thu Nguyen-Phuoc , Douglas Lanman , James Tompkin , Lei Xiao

Implicit neural representations (INRs) have achieved remarkable success in image representation and compression, but they require substantial training time and memory. Meanwhile, recent 2D Gaussian Splatting (GS) methods (\textit{e.g.},…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Tiantian Li , Xinjie Zhang , Xingtong Ge , Tongda Xu , Dailan He , Jun Zhang , Yan Wang

We present LocoGS, a locality-aware 3D Gaussian Splatting (3DGS) framework that exploits the spatial coherence of 3D Gaussians for compact modeling of volumetric scenes. To this end, we first analyze the local coherence of 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Seungjoo Shin , Jaesik Park , Sunghyun Cho

We present a methodology to determine the best turbulence closure for an eddy-permitting ocean model through measurement of the error-landscape of the closure's subgrid spectral transfers and flux. We apply this method to 6 different…

Fluid Dynamics · Physics 2015-06-05 Jonathan Pietarila Graham , Todd Ringler

Topological entropy serves as a viable candidate for quantifying mixing and complexity of a highly chaotic system. Particularly in turbulence, this is determined as the exponential stretching rate of a fluid material line that typically…

Fluid Dynamics · Physics 2026-03-12 Ankan Biswas , Amal Manoharan , Ashwin Joy

Gaussian Splatting and its dynamic extensions are effective for reconstructing 3D scenes from 2D images when there is significant camera movement to facilitate motion parallax and when scene objects remain relatively static. However, in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Liuyue Xie , Joel Julin , Koichiro Niinuma , Laszlo A. Jeni

We reconsider some fundamental aspects of the fluid mechanics model, and the derivation of continuum flow equations from gas kinetic theory. Two topologies for fluid representation are presented, and a set of macroscopic equations are…

Fluid Dynamics · Physics 2007-05-23 S. Kokou Dadzie , Jason M. Reese , Colin R. McInnes

This paper shows that the topological structures of particle orbits generated by a generic class of vector fields on spherical surfaces, called {\it the flow of finite type}, are in one-to-one correspondence with discrete structures such as…

Dynamical Systems · Mathematics 2022-08-18 Takashi Sakajo , Tomoo Yokoyama

Modal and nonmodal analyses of fluid flows provide fundamental insight into the early stages of transition to turbulence. Eigenvalues of the dynamical generator govern temporal growth or decay of individual modes, while singular values of…

Fluid Dynamics · Physics 2021-06-02 Gokul Hariharan , Satish Kumar , Mihailo R. Jovanović

The goal of this work is apply field theory methods to discuss turbulence in relativistic real fluids. We shalltake as representtive model an Israel-Stewart framework, where the conservation laws for the energy-momentum tensor are…

Fluid Dynamics · Physics 2026-05-26 Esteban Calzetta

The Hamiltonian dynamics of a compressible inviscid fluid is formulated as a gauge theory. The idea of gauge equivalence is exploited to unify the study of apparantly distinct physical problems and solutions of new models can be generated…

High Energy Physics - Theory · Physics 2007-05-23 Subir Ghosh

We propose an effective anisotropic fluid description for a generic infrared-modified theory of gravity. In our framework, the additional component of the acceleration, commonly attributed to dark matter, is explained as a radial pressure…

General Relativity and Quantum Cosmology · Physics 2017-12-06 Mariano Cadoni , Roberto Casadio , Andrea Giusti , Wolfgang Mück , Matteo Tuveri

Fully developed turbulence is analised with the lattice model employing vortex tube representation which is introduced recently by the authors. Several characteric features observed in experiments and direct numeric integrations are…

Condensed Matter · Physics 2007-05-23 Y-h. Taguchi , Hideki Takayasu

Lattice-Boltzmann methods are established mesoscopic numerical schemes for fluid flow, that recover the evolution of macroscopic quantities (viz., velocity and pressure fields) evolving under macroscopic target equations. The approximated…