Machine learning is revolutionizing fundamental science by tackling long-standing mathematical challenges. A key example is ...

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

IN recent years great advances have been made in our knowledge of the fundamental structures of analysis, particularly of algebra and topology, and an exposition of Lie groups from the modern point of ...

DeepSeek researchers have developed a technology called Manifold-Constrained Hyper-Connections, or mHC, that can improve the performance of artificial intelligence models. The Chinese AI lab debuted ...

New research indicates that the structural organization of the human brain does not develop in a continuous, linear fashion ...

Abstract: This article proposes a fully analytical synthesis methodology for manifold multiplexers (MUXs). The core of this proposed method involves approximating the dispersive transmission line (TL) ...

DeepSeek has introduced Manifold-Constrained Hyper-Connections (mHC), a novel architecture that stabilizes AI training and ...

This repository contains the official implementation of Discrete Alignment Theory (DAT), focusing on the topological resilience of the $H_3$ manifold projected from ...

Researchers have achieved a significant breakthrough in quantum materials, potentially setting the stage for advancements in topological superconductivity and robust quantum computing. Researchers at ...

Topological matter refers to systems in which topology is required for their characterisation. This includes materials with topological defects such as skyrmions, or topologically-protected edge modes ...

Abstract: Unmanned aerial vehicles (UAVs) have been demonstrated immense potentials to enhance communication systems tailored to the unique characteristics by optimizing the placement and mobility.

What is it about? Evaluation of topology-aware image segmentation often exhibit flawed practices that skew results. In this work, we identify critical pitfalls in model evaluation that include ...