Results 71 to 80 of about 8,389,880 (297)
Online Quantum Mixture Regression for Trajectory Learning by Demonstration [PDF]
, 2013 16/01/14 MEB. Pre-print version OK to add.In this work, we present the online Quantum Mixture Model (oQMM), which combines the merits of quantum mechanics and stochastic optimization. More specifically it allows for quantum effects on the mixture states,
Dimitrios Korkinof +3 more
core +1 more source
Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
Advanced Functional Materials, EarlyView.Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang +3 more
wiley +1 more source
Taking advantage of noise in quantum reservoir computing
Scientific Reports, 2023 The biggest challenge that quantum computing and quantum machine learning are currently facing is the presence of noise in quantum devices. As a result, big efforts have been put into correcting or mitigating the induced errors. But, can these two fields
L. Domingo, G. Carlo, F. Borondo
doaj +1 more source
Full quantum dynamics with machine learning
, 2022 The data provided here is for the case studies given in Chapter "Excited-state dynamics with machine learning " Book: "Quantum Chemistry in the Age of Machine Learning" https://www.elsevier.com/books/quantum-chemistry-in-the-age-of-machine-learning ...
Arif Ullah (11249346) +1 more
core +1 more source
Verifying Fairness in Quantum Machine Learning
, 2022 AbstractDue to the beyond-classical capability of quantum computing, quantum machine learning is applied independently or embedded in classical models for decision making, especially in the field of finance. Fairness and other ethical issues are often one of the main concerns in decision making.
Ji Guan 0001 +2 more
openaire +3 more sources
An Adaptive Inhibitory WSe2 Transistor for Retinomorphic In‐Sensor Image Processing
Advanced Functional Materials, EarlyView.Conventional retinomorphic devices typically require deliberate gate‐bias tuning for each illumination condition. In this paper, we demonstrate an adaptive inhibitory WSe2 transistor that uses photo‐induced regime shift between the subthreshold and accumulation modes to achieve decision‐free, intensity‐adaptive image processing within a single pixel ...
Juhwan Baek +12 more
wiley +1 more source
Machine Learning and Knowledge ExtractionQuantum computing, with its foundational principles of superposition and entanglement, has the potential to provide significant quantum advantages, addressing challenges that classical computing may struggle to overcome.
Maria Revythi, Georgia Koukiou
doaj +1 more source
Advanced Functional Materials, EarlyView.Unlocking thermomagnetic low‐grade waste heat recovery. This perspective provides a comprehensive roadmap for the development of thermomagnetic materials and systems. By addressing key engineering challenges across multiple scales, it bridges the gap between micro‐power IoT devices and large‐scale industrial applications. ABSTRACT Nearly half of global
A. Waske +13 more
wiley +1 more source
On Quantum Methods for Machine Learning Problems Part II: Quantum Classification Algorithms
Big Data Mining and Analytics, 2020 This is a review of quantum methods for machine learning problems that consists of two parts. The first part, "quantum tools", presented some of the fundamentals and introduced several quantum tools based on known quantum search algorithms.
Farid Ablayev +5 more
doaj +1 more source
Clinical data classification with noisy intermediate scale quantum computers
Scientific Reports, 2022 Quantum machine learning has experienced significant progress in both software and hardware development in the recent years and has emerged as an applicable area of near-term quantum computers.
S. Moradi +7 more
doaj +1 more source