Related papers: The view from the boundary: a new void stacking me…
This paper addresses the problem of detecting boundary points and estimating the sampling density of a dataset derived from a compact manifold with boundary, potentially in the presence of noise. We extend recent advances in doubly…
Using deep learning, this paper addresses the problem of joint object boundary detection and boundary motion estimation in videos, which we named boundary flow estimation. Boundary flow is an important mid-level visual cue as boundaries…
We investigate the properties of one--dimensional flux ``voids'' (connected regions in the flux distribution above the mean flux level) by comparing hydrodynamical simulations of large cosmological volumes with a set of observed…
We review and discuss aspects of Cosmic Voids that form the background for our Void Galaxy Survey (see accompanying paper by Stanonik et al.). Following a sketch of the general characteristics of void formation and evolution, we describe…
Particle-based boundary representations are frequently used in Smoothed Particle Hydrodynamics (SPH) due to their simple integration into fluid solvers. Commonly, incompressible fluid solvers estimate the current density and corresponding…
We present a novel framework to deal with static and moving immersed boundaries (IB). In this strategy, called Volume-Filtering Immersed Boundary (VFIB) method, transport equations are derived by filtering the Navier-Stokes equations and…
LiDAR is an important method for autonomous driving systems to sense the environment. The point clouds obtained by LiDAR typically exhibit sparse and irregular distribution, thus posing great challenges to the detection of 3D objects,…
We develop models of void formation starting from a small initial fluctuation at recombination and growing to a realistic present day density profile in agreement with observations of voids. The model construction is an extension of…
Friction drag from a turbulent fluid moving past or inside an object plays a crucial role in domains as diverse as transportation, public utility infrastructure, energy technology, and human health. As a direct measure of the shear-induced…
Vision-based roadside 3D object detection has attracted rising attention in autonomous driving domain, since it encompasses inherent advantages in reducing blind spots and expanding perception range. While previous work mainly focuses on…
The fabric of porous and fractured media contains solid regions (grains) and voids. The space conducting fluids is a system of connected voids with variable geometries. Relative to the grain sizes, the voids can be voluminous with three…
We investigate the impact of filament and void environments on galaxies, looking for residual effects beyond the known relations with environment density. We quantified the host environment of galaxies as the distance to the spine of the…
We present a new methodology for detecting out-of-distribution (OOD) images by utilizing norms of the score estimates at multiple noise scales. A score is defined to be the gradient of the log density with respect to the input data. Our…
In the rapidly rotating limit, we derive a balanced set of reduced equations governing the strongly nonlinear development of the convective wall-mode instability in the interior of a general container. The model illustrates that wall-mode…
Numerous processes across both the physical and biological sciences are driven by diffusion. Partial differential equations (PDEs) are a popular tool for modelling such phenomena deterministically, but it is often necessary to use…
One of the most striking features in galaxy redshift surveys is the ubiquitous presence of voids. However, voids have not been extensively studied due to observational limitations. Until recently, galaxy redshift surveys included only a few…
Cosmic voids are promising cosmological laboratories for studying the dark energy phenomenon and alternative gravity theories. They are receiving special attention nowadays in view of the new generation of galaxy spectroscopic surveys,…
In the study of high-dimensional data, it is often assumed that the data set possesses an underlying lower-dimensional structure. A practical model for this structure is an embedded compact manifold with boundary. Since the underlying…
We show that the theory of varifolds can be suitably enriched to open the way to applications in the field of discrete and computational geometry. Using appropriate regularizations of the mass and of the first variation of a varifold we…
Scene flow estimation is the task to predict the point-wise or pixel-wise 3D displacement vector between two consecutive frames of point clouds or images, which has important application in fields such as service robots and autonomous…