Results 81 to 90 of about 5,645 (242)
Arthritis Care &Research, EarlyView.Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah +4 more
wiley +1 more source
8. Bilevel approaches for learning of variational imaging models
, 2016 We review some recent learning approaches in variational imaging based on bilevel optimization and emphasize the importance of their treatment in function space. The paper covers both analytical and numerical techniques.
Juan Carlos De los Reyes +4 more
core +1 more source
Frontiers in PhysicsOptimal control in open quantum systems is considered, with a focus on a two-level logical qubit system whose time evolution is governed by Markovian dynamics described within the Lindblad (GKSL) formalism.
Sonet Daniel Thomas +12 more
doaj +1 more source
Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
International Journal of Adaptive Control and Signal Processing, EarlyView.This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
Evolutionary Variational Optimization for Probabilistic Unsupervised Learning [PDF]
, 2022 Probabilistic generative modeling is a powerful machine learning paradigm suitable for a variety of tasks, such as missing value estimation, denoising, clustering, outlier detection, or compression.
Drefs, Jakob
core
Learning Topological States from Randomized Measurements Using Variational Tensor-Network Tomography
PRX QuantumLearning faithful representations of quantum states is crucial to fully characterizing the variety of many-body states created on quantum processors. While various tomographic methods, such as classical shadow and matrix product state (MPS) tomography ...
Yanting Teng +7 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Bilevel approaches for learning of variational imaging models
, 2017 We review some recent learning approaches in variational imaging based on bilevel optimization and emphasize the importance of their treatment in function space. The paper covers both analytical and numerical techniques.
De los Reyes J.C. +4 more
core
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Adaptive measurement strategy for quantum subspace methods
New Journal of PhysicsEstimation of physical observables for unknown quantum states is an important problem that underlies a wide range of fields, including quantum information processing, quantum physics, and quantum chemistry.
Yuma Nakamura +2 more
doaj +1 more source