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2,497 papers
Abstract Given the state of a subject and the state of the environment he is in, under what conditions does the question "what should be done next" have a determinate answer, and where does that answer lie. This paper gives a computable form and marks out its domain of definition. First, location on three axes. The sta...
The integration of Computational Materials Science (CMS) and Machine Learning (ML)/Artificial Intelligence (AI) techniques, along with Accelerated High-Performance Computing (AHPC) achieved using modern hardware accelerators such as GPUs, provides a powerful platform for researchers to accelerate advancements in Materi...
Current research provides an overview of important QML algorithms, such as Quantum Support Vector Machines (QSVM), Quantum Neural Networks (QNN), Variational Quantum Eigensolvers (VQE), Quantum Approximate Optimization Algorithm (QAOA), and hybrid quantumclassical computing techniques, which have recently become more p...
Background Bipolar intuitionistic fuzzy graphs (BIFGs) extend fuzzy graphs by assigning both positive and negative membership and non-membership degrees to vertices and edges, capturing more nuanced uncertainty. The chromatic number of a BIFG, unlike that of crisp graphs, depends on the interplay of these bipolar param...
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Large ground-based astronomical telescopes deliver blurry images due to perturbations introduced by Earth's atmosphere. To recover sharp images, these distortions must be optically corrected in real time by an adaptive optics (AO) system. The control system that performs this task must operate thousands of optical sens...
Spacecrafts gather more data than they can send back to Earth. When a satellite is in low earth orbit, it can be in contact with a ground station for just a few minutes during one orbit while constantly collecting data from its instruments, and a large portion of the data gathered is wasted due to cloud obstruction or...
Author: Yoko Hasebe (Iwakuni, Yamaguchi, Japan) Date: September 2026 Classification: Open Architecture Specification & Technical White Paper Abstract: Modern cyber-physical infrastructure—encompassing power grids, telecommunications, and distributed energy resources (DERs)—is increasingly interfacing with frontier AI i...
986 laser back-scatter scan records acquired from nine industrial materials with a sub-milliwatt Class II laser diode at 635 nm, together with a record-level manifest. The dataset accompanies the article Optical non-destructive identification of industrial materials from low-power laser back-scatter. Acquisition. A two...
The integration of Computational Materials Science (CMS) and Machine Learning (ML)/Artificial Intelligence (AI) techniques, along with Accelerated High-Performance Computing (AHPC) achieved using modern hardware accelerators such as GPUs, provides a powerful platform for researchers to accelerate advancements in Materi...
The AV-IMAP Simulator is a MATLAB-based computational tool for evaluating solar irradiance and shading characteristics of agrivoltaic (AV) panel configurations. The model is developed to compute the spatial and temporal distribution of direct, diffuse, total ground irradiance beneath photovoltaic (PV) arrays, and AV an...
Spacecrafts gather more data than they can send back to Earth. When a satellite is in low earth orbit, it can be in contact with a ground station for just a few minutes during one orbit while constantly collecting data from its instruments, and a large portion of the data gathered is wasted due to cloud obstruction or...
A stability‐centered framework is established to systematically untangle the multi‐dimensional failure mechanisms across four primary sensing modalities, including ion‐selective potentiometric, enzymatic, nanozyme‐based, and affinity‐based sensors.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
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