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Three-dimensional (3D) maps of the Galactic interstellar matter (ISM) are a potential tool of wide use, however accurate and detailed maps are still lacking. One of the ways to construct the maps is to invert individual distance-limited ISM…

Astrophysics of Galaxies · Physics 2015-06-17 Rosine Lallement , Jean-Luc Vergely , Bernard Valette , Lucky Puspitarini , Laurent Eyer , Luca Casagrande

This paper proposes a new 3D gas distribution mapping technique based on the local message passing of Gaussian belief propagation that is capable of resolving in real time, concentration estimates in 3D space whilst accounting for the…

Robotics · Computer Science 2023-03-07 Callum Rhodes , Cunjia Liu , Wen-Hua Chen

Recent advances in 3D Gaussian diffusion models suffer from time-intensive denoising and post-denoising processing due to the massive number of Gaussian primitives, resulting in slow generation and limited scalability along sampling…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Zeyuan Yin , Xiaoming Liu

While 3D Gaussian Splatting (3DGS) has demonstrated remarkable performance in novel view synthesis and real-time rendering, the high memory consumption due to the use of millions of Gaussians limits its practicality. To mitigate this issue,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Yifei Liu , Zhihang Zhong , Yifan Zhan , Sheng Xu , Xiao Sun

We reconsider a nonparametric density model based on Gaussian processes. By augmenting the model with latent P\'olya--Gamma random variables and a latent marked Poisson process we obtain a new likelihood which is conjugate to the model's…

Machine Learning · Statistics 2018-05-30 Christian Donner , Manfred Opper

Approximation algorithms are widely used in many engineering problems. To obtain a data set for approximation a factorial design of experiments is often used. In such case the size of the data set can be very large. Therefore, one of the…

Methodology · Statistics 2014-07-04 Mikhail Belyaev , Evgeny Burnaev , Yermek Kapushev

Multivariate Gaussian processes (GPs) offer a powerful probabilistic framework to represent complex interdependent phenomena. They pose, however, significant computational challenges in high-dimensional settings, which frequently arise in…

Fitting a theoretical model to experimental data in a Bayesian manner using Markov chain Monte Carlo typically requires one to evaluate the model thousands (or millions) of times. When the model is a slow-to-compute physics simulation,…

Machine Learning · Statistics 2022-08-25 Steven Stetzler , Michael Grosskopf , Earl Lawrence

Gaussian processes provide a flexible framework for spatial prediction, but their computational cost limits applicability to large-scale data with large sample size $n$. Predictive processes (PPs), a popular low-rank approximation, mitigate…

Methodology · Statistics 2026-03-23 Nicolas Bianco , Nadja Klein

Recent advances in 3D Gaussian Splatting (3DGS) have demonstrated remarkable capabilities in real-time and photorealistic novel view synthesis. However, traditional 3DGS representations often struggle with large-scale scene management and…

Graphics · Computer Science 2025-08-08 Zijian Wang , Beizhen Zhao , Hao Wang

The use of Gaussian processes (GPs) is supported by efficient sampling algorithms, a rich methodological literature, and strong theoretical grounding. However, due to their prohibitive computation and storage demands, the use of exact GPs…

Statistics Theory · Mathematics 2022-07-27 Kelly R. Moran , Matthew W. Wheeler

Spatio-temporal systems exhibiting multi-scale behaviour are common in applications ranging from cyber-physical systems to systems biology, yet they present formidable challenges for computational modelling and analysis. Here we consider a…

Quantitative Methods · Quantitative Biology 2019-02-01 Michalis Michaelides , Jane Hillston , Guido Sanguinetti

The increased demand for online prediction and the growing availability of large data sets drives the need for computationally efficient models. While exact Gaussian process regression shows various favorable theoretical properties…

Machine Learning · Computer Science 2021-08-02 Armin Lederer , Alejandro Jose Ordonez Conejo , Korbinian Maier , Wenxin Xiao , Jonas Umlauft , Sandra Hirche

Results. We illustrate our profile-fitting technique and present the K\,{\sc i} velocity structure of the dense ISM along the paths to all targets. As a validation test of the dust map, we show comparisons between distances to several…

Astrophysics of Galaxies · Physics 2021-08-04 A. Ivanova , R. Lallement , J. L. Vergely , C. Hottier

The next generation of Department of Energy supercomputers will be capable of exascale computation. For these machines, far more computation will be possible than that which can be saved to disk. As a result, users will be unable to rely on…

Machine Learning · Computer Science 2025-07-23 Michael Grosskopf , Kellin Rumsey , Ayan Biswas , Earl Lawrence

We have constructed a full-sky map of the far-infrared suitable for measuring Galactic reddening and extinction (Schlegel, Finkbeiner & Davis 1998: SFD). The SFD map is based upon extensive re-analysis of data from the COBE/DIRBE and IRAS…

Astrophysics · Physics 2007-05-23 D. J. Schlegel , D. P. Finkbeiner , M. Davis

To investigate the evolution of dust in a cosmological volume, we perform hydrodynamic simulations, in which the enrichment of metals and dust is treated self-consistently with star formation and stellar feedback. We consider dust evolution…

Astrophysics of Galaxies · Physics 2018-07-24 Shohei Aoyama , Kuan-Chou Hou , Hiroyuki Hirashita , Kentaro Nagamine , Ikkoh Shimizu

Using a grid of empirically calibrated synthetic spectra developed in our previous study, we construct an all-sky 3D extinction map from the large collection of low-resolution XP spectra in Gaia DR3. Along each line of sight, with an area…

Astrophysics of Galaxies · Physics 2024-09-27 Deokkeun An , Timothy C. Beers , Anirudh Chiti

Neutral hydrogen (HI) emission closely traces the dust column density at high Galactic latitudes and is thus a powerful tool for predicting dust extinction. However, the relation between HI column density $N_{\rm HI}$ and high-latitude dust…

Astrophysics of Galaxies · Physics 2025-04-28 Yun-Ting Cheng , Brandon S. Hensley , Tzu-Ching Chang , Olivier Doré

Large-scale precision matrix estimation is of fundamental importance yet challenging in many contemporary applications for recovering Gaussian graphical models. In this paper, we suggest a new approach of innovated scalable efficient…

Methodology · Statistics 2016-05-12 Yingying Fan , Jinchi Lv
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