A new technique that efficiently retrieves scattered light from fluorescent sources can be used to record neuronal signals coming from deep within the brain. The technique, developed by physicists at ...

High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...

AS a finite dimensional linear space over the rational number field ℚ, an algebraic number field is of particular importance and interest in mathematics and engineering. Algorithms using algebraic ...

Abstract. In this paper, an iterative method is presented to solve the linear matrix equation AXB = C over the generalized reflexive (or anti-reflexive) matrix X (A ∈ Rp×n; B ∈ Rm×q, C ∈ Rp×q, X ∈ ...

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...

Enhances Model Authoring Efficiency and Simulation Performance Utilizing Multicore Capabilities MOUNTAIN VIEW, Calif., March 3, 2010 -- Synopsys, Inc. (Nasdaq: SNPS), a world leader in software and IP ...

The belief that we are living in a Matrix-like simulation has has grown traction in recent years, but boffins believe they ...

A Hong Kong-based Matrix AI Network is developing a prototype of a new hybrid PoS/PoW consensus algorithm. This update was shared with Cointelegraph by Owen Tao, the company’s CEO. Tao described ...