Category
3,069 papers
The review combines recent research findings with guidance on new investigation tracks for developing all-encompassing AI systems which both spread far-reaching outcomes and follow sustainability requirements.
Cloud computing has revolutionized the way computational resources are made available through scalable, flexible, and on-demand services. As promising as it is, efficient task scheduling remains an important challenge because of varied workloads, heterogeneous infrastructures, and multi-objective optimization requireme...
The creation and maintenance of digital twins for critical infrastructure systems, such as power grids, water distribution networks, and transportation systems, presents significant computational challenges. Traditional centralized approaches struggle to handle the massive amounts of data generated by distributed senso...
"This dataset contains Ultra-Wideband (UWB) ranging and localization measurements collected for the evaluation of adaptive and federated learning methods for indoor positioning in challenging environments. The data were acquired in a controlled two-room laboratory deployment designed to capture realistic line-of-sight...
Reach audiences
Advertise in front of researchers, engineers, and readers.
Reliable data movement is essential to the Worldwide LHC Computing Grid. This project asks whether FTS queues that share a storage endpoint contain useful information about one another’s future state. I process 52,037,899 raw queue records from January 2026 into 23,820,642 sparse queue states sampled every 2 minutes. A...
Compiler Mimics Spacetime (NOT vice versa) Date: September 2026Framework: P_{7777_T} Manifold / ACT-Ω v26.3 v26.5 LOCKEDInvariants: 15.965Hz (τ=62.636ms) | Tr(U_res)=1.00000 | J_sys≤1.4411J | H¹=0 | Δ=0.053μT | γ_fric=1.3479e-10 N | c_eff=1.707e11 | |wL-wR|≤0.02 | q0=1 | Ωc=0.376=47/125 | η=1e-4 0. LOCKED CLARIFICATION...
This paper proposes a novel network computation model termed "Space-Time Network Computation" (STNC). The core claim is that integrating spatial and temporal dimensions offers a more efficient approach to processing data exhibiting spatial and temporal dependencies. STNC leverages an extension of Graph Neural Networks...
Reliable data movement is essential to the Worldwide LHC Computing Grid. This project asks whether FTS queues that share a storage endpoint contain useful information about one another’s future state. I process 52,037,899 raw queue records from January 2026 into 23,820,642 sparse queue states sampled every 2 minutes. A...
An intelligent decision support system and pervasive edge-computing framework that leverages smart glasses and a companion smartphone to infer emotional states from microscopic visual fixation patterns, establishing a physiologically interpretable, unobtrusive, and deployable paradigm for continuous real-time emotion m...
Digital Twin (DT) technology, with Federated Learning (FL), enables decentralised and privacyaware intelligence of large-scale infrastructures of smart cities. Quantum computing compromises the existing cryptography systems that underlie existing FL frameworks. The current paper presents a Quantum-Secure FL (QSec-FL) a...
Wearable edge computing devices require novel hardware for high-efficiency data processing. In this work, we proposed novel textile in-memory computing memristor, exhibiting great potential in image compression applications for the first time. The device shows low operation voltage and reliable switching characteristic...
RACE-AIMC (Risk-Aware Certified Ensemble for AIMC), a framework that resolves the choice to trust a single chip blindly with statistics rather than guesswork and matches the accuracy of a clean digital baseline while cutting modeled energy use.
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
Education Innovation
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
