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A study led by the University of Oxford has used the power of machine learning to overcome a key challenge affecting quantum devices. For the first time, the findings reveal a way to close the ‘reality gap’: the difference between predicted and observed behaviour from quantum devices. The results have been published in Physical Review X.
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New study uses machine learning to bridge the reality gap in quantum devices
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Breakthrough promises secure quantum computing at home Study of Laser-Induced Multi-Exciton Generation and Dynamics by Multi-Photon Absorption in CdSe Quantum Dots In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back Towards blockchain based federated learning in categorizing healthcare monitoring devices on artificial intelligence of medical things investigative framework Spintronics-Based Neuromorphic and Ising Computing Cardiovascular disease risk assessment through sensing the circulating microbiome with perovskite quantum dots leveraging deep learning models for bacterial species selection Virtual Reality Simulation for Medical Educators ORA collection on AI & Machine Learning launch event Training an Ising machine with equilibrium propagation QUANTUM FURY Wargame, Cyber Cup Rematch Range-separated density functional theory using multiresolution analysis and quantum computing The application of virtual reality and augmented reality in dentistry - a literature review Trustworthy Precision Medicine: An Interpretable Approach to Detecting Anomalous Behavior of IoT Devices Two-Terminal Perovskite Optoelectronic Synapse for Rapid Trained Neuromorphic Computation with High Accuracy Computed tomography machine learning classifier correlates with mortality in interstitial lung disease Investigating Machine Learning Techniques for Predicting Risk of Asthma Exacerbations: A Systematic Review Low hysteresis, water retention, anti-freeze multifunctional hydrogel strain sensor for human-machine interfacing and real-time sign language translation The Ethics of Electronic Tracking Devices in Dementia Care: An Interview Study with Developers 2024 Maurice Lubbock Memorial Lecture Machine learning, deep learning and hernia surgery. 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New study uses machine learning to bridge the reality gap in quantum devices
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New study uses machine learning to bridge the reality gap in quantum devices
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AI Virtual Reality Related Evidence Matrix
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A qualitative systematic review Parent's perception of digital device use among their preschool children and its associated factors in Kota Setar, Kedah Professor John Cardy awarded Breakthrough Prize in Fundamental Physics Extended Reality-Based Mobile App Solutions for the Therapy of Children With Autism Spectrum Disorders: Systematic Literature Review Extended Reality-Based Mobile App Solutions for the Therapy of Children With Autism Spectrum Disorders: Systematic Literature Review A primer on the use of machine learning to distil knowledge from data in biological psychiatry An overview of clinical machine learning applications in neurology Wearable Devices to Improve Physical Activity and Reduce Sedentary Behaviour: An Umbrella Review Digital remote monitoring for screening and early detection of urinary tract infections Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures Suitability of the Current Health Technology Assessment of Innovative Artificial Intelligence-Based Medical Devices: Scoping Literature Review Consumer-Grade Electroencephalogram and Functional Near-Infrared Spectroscopy Neurofeedback Technologies for Mental Health and Wellbeing The use of machine learning on administrative and survey data to predict suicidal thoughts and behaviors: a systematic review Quantum projections on conceptual subspaces: A deeper dive into methodological challenges and opportunities Virtual Reality-Based Education Program for Managing Behavioral and Psychological Symptoms of Dementia: Development and Feasibility Test Firearm locking device preferences among firearm owners in the USA: a systematic review Learning Experience Design and Unpacking Sociocultural, Technological, and Pedagogical Design Considerations of Spherical Video-Based Virtual Reality Systems for Autistic Learners: A Systematic Literature Review Characterization of pathogenic factors for premenstrual dysphoric disorder using machine learning algorithms in rats 2024 Oxford University of Sanctuary Fair Machine learning in internet financial risk management: A systematic literature review Large Language Model-Based AI Agent for Organic Semiconductor Devices Research Optical fiber sensors for posture monitoring, ulcer detection and control in a wheelchair: a state-of-the-art High-Performance Graphene Flexible Sensors for Pulse Monitoring and Human-Machine Interaction Utilizing machine learning to facilitate the early diagnosis of posterior circulation stroke The added value of devices to pelvic floor muscle training in radical post-prostatectomy stress urinary incontinence: A systematic review with metanalysis Accuracy of portable ultrasound for obstetric biometry