Abstract: In multi-label recognition tasks, convolutional neural networks (CNNs) can extract rich features of images in Euclidean space. However, CNNs struggle to handle dependencies between ...

In the mid-19th century, Bernhard Riemann conceived of a new way to think about mathematical spaces, providing the foundation ...

Detailed price information for Euclidean Fundamental Value ETF (ECML-A) from The Globe and Mail including charting and trades.

Detailed price information for Euclidean Fundamental Value ETF (ECML-A) from The Globe and Mail including charting and trades.

(via Quanta Magazine) Mathematician Maggie Miller explores the strange and fascinating world of 4D topology — the study of shapes, or manifolds, that resemble flat Euclidean space when viewed up close ...

ABSTRACT: In this paper, a class of Choquard equation with Hardy potential in the whole space ℝ N will be considered, where the parameters p , q and α in the convolution-nonlinearity term are under a ...

The aim of the paper is to show the fundamental advantage of the Euclidean Model of Space and Time (EMST) over Special Relativity (SR) in the field of wave description of matter. The EMST offers a ...

2Dの分子グラフ表現を3Dの潜在空間に落とし込んだ上で拡散モデルを適用する分子生成手法。オートエンコーダも合わせて学習し、3D潜在空間から2D分子へと変換する。離散空間から連続空間 ...

Introduction: Brain computer interfaces (BCI), which establish a direct interaction between the brain and the external device bypassing peripheral nerves, is one of the hot research areas. How to ...

Do black holes, like dying old soldiers, simply fade away? Do they pop like hyperdimensional balloons? Maybe they do, or maybe they pass through a cosmic rubicon, effectively reversing their natures ...

Olgica Milenkovic’s group has been developing machine learning approaches that can tell revealing new stories about biological phenomena—but her work has very old roots. Written by Olgica Milenkovic’s ...