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3D Gaussian Splatting (3DGS) has achieved excellent rendering quality with fast training and rendering speed. However, its optimization process lacks explicit geometric constraints, leading to suboptimal geometric reconstruction in regions…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Lin-Zhuo Chen , Kangjie Liu , Youtian Lin , Siyu Zhu , Zhihao Li , Xun Cao , Yao Yao

Using symbolic regression to discover physical laws from observed data is an emerging field. In previous work, we combined genetic algorithm (GA) and machine learning to present a data-driven method for discovering a wave equation. Although…

Geophysics · Physics 2024-04-30 Shijun Cheng , Tariq Alkhalifah

Gaussian beams are asymptotically valid high frequency solutions to hyperbolic partial differential equations, concentrated on a single curve through the physical domain. They can also be extended to some dispersive wave equations, such as…

Numerical Analysis · Mathematics 2011-06-03 Hailiang Liu , Olof Runborg , Nicolay M. Tanushev

3D Gaussian Splatting (3D-GS) enables efficient novel view synthesis, but treats all frequencies uniformly, making it difficult to separate coarse structure from fine detail. Recent works have started to exploit frequency signals, but lack…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Yishai Lavi , Leo Segre , Shai Avidan

Structured data, such as graphs, is vital in machine learning due to its capacity to capture complex relationships and interactions. In recent years, the Fused Gromov-Wasserstein (FGW) distance has attracted growing interest because it…

Machine Learning · Computer Science 2025-09-29 Yikun Bai , Shuang Wang , Huy Tran , Hengrong Du , Juexin Wang , Soheil Kolouri

Accurately simulating the atmospheric turbulence behaviour is always challenging. The well-known FFT based method falls short in correctly predicting both the low and high frequency behaviours. Sub-harmonic compensation aids in…

Instrumentation and Methods for Astrophysics · Physics 2022-08-15 Sorabh Chhabra , Jyotirmay Paul , A. N. Ramaprakash , Avinash Surendran

We consider learning Ising tree models when the observations from the nodes are corrupted by independent but non-identically distributed noise with unknown statistics. Katiyar et al. (2020) showed that although the exact tree structure…

Machine Learning · Statistics 2021-01-25 Anshoo Tandon , Aldric H. J. Yuan , Vincent Y. F. Tan

Existing theoretical results for attenuation of surface waves propagating on water of random fluctuating depth are shown to over predict the rate of decay due to the way in which ensemble averaging is performed. A revised approach is…

Fluid Dynamics · Physics 2026-03-05 Lloyd Dafydd , Richard Porter

Exponential approximation based on the first order mean spherical approximation (FMSA) is applied to the study of the structure and thermodynamics of hard-core repulsive Yukawa fluids. The proposed theory utilizes an exponential enhancement…

Soft Condensed Matter · Physics 2012-07-13 S. Hlushak , A. Trokhymchuk

We suggest a new method of calculation of the equilibrium correlation functions of an arbitrary order for the interacting Fermi-gas model in the frame of the static fluctuation approximation (SFA) method. This method based only on the…

Strongly Correlated Electrons · Physics 2015-05-27 R. R. Nigmatullin , A. A. Khamzin , I. I. Popov

Recent progress in synthetic aperture sonar (SAS) technology and processing has led to significant advances in underwater imaging, outperforming previously common approaches in both accuracy and efficiency. There are, however, inherent…

Numerical Analysis · Mathematics 2017-06-28 John McKay , Anne Gelb , Vishal Monga , Raghu Raj

The nonlinear interaction between electromagnetic, electrostatic and gravitational waves in a Vlasov plasma is reconsidered. By using a orthonormal tetrad description the three-wave coupling coefficients are computed. Comparing with…

General Relativity and Quantum Cosmology · Physics 2015-05-14 G. Brodin , M. Forsberg , M. Marklund , D. Eriksson

We present three-dimensional simulations of Einstein equations implementing a symmetric hyperbolic system of equations with dynamical lapse. The numerical implementation makes use of techniques that guarantee linear numerical stability for…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Manuel Tiglio , Luis Lehner , David Neilsen

We construct high-frequency initial data for the Einstein vacuum equations in dimension 3+1 by solving the constraint equations on $\mathbb{R}^3$. Our family of solutions $(\bar{g}_\lambda,K_\lambda)_{\lambda\in(0,1]}$ is defined through a…

General Relativity and Quantum Cosmology · Physics 2023-05-17 Arthur Touati

3D Gaussian splatting has achieved very impressive performance in real-time novel view synthesis. However, it often suffers from over-reconstruction during Gaussian densification where high-variance image regions are covered by a few large…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Jiahui Zhang , Fangneng Zhan , Muyu Xu , Shijian Lu , Eric Xing

Although the accurate description of the wave propagation and absorption in plasmas requires complicated full wave solutions or kinetic simulations, the local dispersion analysis can still be helpful to capture the main physics of wave…

Plasma Physics · Physics 2024-05-01 Huasheng Xie , Haojie Ma , Yukun Bai

Branches swaying in the breeze, flags rippling in the wind, and boats rocking on the water all show how aerodynamics shape natural motion -- an effect crucial for realism in vision and graphics. In this paper, we present Gaussian Swaying, a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Hongru Yan , Xiang Zhang , Zeyuan Chen , Fangyin Wei , Zhuowen Tu

3D Gaussian Splatting (3DGS) has recently advanced radiance field reconstruction by offering superior capabilities for novel view synthesis and real-time rendering speed. However, its strategy of blending optimization and adaptive density…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Rong Liu , Rui Xu , Yue Hu , Meida Chen , Andrew Feng

Full-Waveform Inversion (FWI) is a nonlinear iterative seismic imaging technique that, by reducing the misfit between recorded and predicted seismic waveforms, can produce detailed estimates of subsurface geophysical properties.…

Geophysics · Physics 2024-11-22 Vahid Negahdari , Seyed Reza Moghadasi , Mohammad Reza Razvan

The automated localisation of damage in structures is a challenging but critical ingredient in the path towards predictive or condition-based maintenance of high value structures. The use of acoustic emission time of arrival mapping is a…

Machine Learning · Computer Science 2023-01-11 Matthew R Jones , Timothy J Rogers , Elizabeth J Cross