|Feature|8-bit|10-bit| |:-|:-|:-| |Shades per channel|256|1024| |Total colors|16.7M|1.07B| |Gradient smoothness|Moderate, banding possible|Very smooth, minimal banding| |HDR support|Limited|Excellent|...
Readability criteria, such as distance or neighborhood preservation, are often used to optimize node-link representations of graphs to enable the comprehension of the underlying data. With few exceptions, graph drawing algorithms typically optimize o...
We define several notions of singular set for Type I Ricci flows and show that they all coincide. In order to do this, we prove that blow-ups around singular points converge to nontrivial gradient shrinking solitons, thus extending work of Naber. As...
In this paper, we define a reduced distance function based at a point at the singular time $T<\infty$ of a Ricci flow. We also show the monotonicity of the corresponding reduced volume based at time T, with equality iff the Ricci flow is a gradient...
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Hey people. Due to some formatting issues with the old posts, I'm now posting these daily news updates as a gallery with a detailed writeup of all the watches down in the comments. It’s a bit messy ...
Oct 18, 2024 · While thermal energy refers to the motion of particles in a substance, heat refers to the flow of thermal energy. It happens when there is a temperature gradient in the substance.
Fibroblast-myocyte coupling can modulate electrical-wave dynamics in cardiac tissue. In diseased hearts, the distribution of fibroblasts is heterogeneous, so there can be gradients in the fibroblast density (henceforth we call this GFD) especially fr...
Spatial variations in the electrical properties of cardiac tissue can occur because of cardiac diseases. We introduce such gradients into mathematical models for cardiac tissue and then study, by extensive numerical simulations, their effects on reen...
Inverse problems generally require a regularizer or prior for a good solution. A recent trend is to train a convolutional net to denoise images, and use this net as a prior when solving the inverse problem. Several proposals depend on a singular valu...
A primal-dual accelerated stochastic gradient descent with variance reduction algorithm (PDASGD) is proposed to solve linear-constrained optimization problems. PDASGD could be applied to solve the discrete optimal transport (OT) problem and enjoys th...
We fit elliptical isophotes to the Hubble Deep Field-North WFPC-2 and NICMOS data to study the rest-frame UV_{218}-U_{300} color profiles and rest-frame B surface brightness profiles of 33 intermediate redshift galaxies (0.5 <= z <= 1.2) with I_{81...
In this article, we address the issue of recovering latent transparent layers from superimposition images. Here, we assume we have the estimated transformations and extracted gradients of latent layers. To rapidly recover high-quality image layers, w...
This project predicts the type of Anaemia in patients using machine learning techniques, specifically the XGBoost algorithm and a Sacking Ensemble Classifier.. After preprocessing the data , we apply XGBoost—a powerful gradient boosting framework known for its accuracy and effici…
This study outlines a light gradient boosted model aimed at predicting shot outcomes in the NHL. The model uses the NHL's spatiotemporal data to account for both the skill of shooters and goaltenders. This approach involves isolating and engineering...
We apply laser light to induce the asymmetric heating of Janus colloids adsorbed at water-oil interfaces and realize active micrometric "Marangoni surfers". The coupling of temperature and surfactant concentration gradients generates Marangoni stress...
A Marangoni surfer is an object embedded in a gas-liquid interface, propelled by gradients in surface tension. We derive an analytical theorem for the lower bound on the viscous dissipation by a Marangoni surfer in the limit of small Reynolds and cap...
(disambiguation) Fader (disambiguation) Gradient (disambiguation) All pages with titles beginning with Fade All pages with titles containing Fade All pages with
An inequality of Brascamp and Lieb provides a bound on the covariance of two functions with respect to log-concave measures. The bound estimates the covariance by the product of the $L^2$ norms of the gradients of the functions, where the magnitude o...