Results 151 to 160 of about 487,019 (287)
Advanced Intelligent Discovery, EarlyView.The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Advanced Intelligent Discovery, EarlyView.Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
Fluctuation theorem for Hamiltonian Systems : Le Chatelier's principle
, 2001 For thermostated dissipative systems, the fluctuation theorem gives an analytical expression for the ratio of probabilities that the time-averaged entropy production in a finite system observed for a finite time takes on a specified value compared to the
Bernhardt, Debra +2 more
core
Advanced Intelligent Discovery, EarlyView.The behaviors of semiflexible polymers such as DNA and protein are often reshaped by coupled interactions. Monte Carlo simulations assist in studying these systems. This work recasts the traditional chain‐growth strategy into a new framework: a fixed number of chains grow synchronously, while less relevant chains to the target system are removed and ...
Yihan Zhao, Jizeng Wang
wiley +1 more source
Quantum fluctuation theorem to benchmark quantum annealers
, 2018 Near term quantum hardware promises unprecedented computational advantage. Crucial in its development is the characterization and minimization of computational errors.
Gardas, Bartlomiej, Deffner, Sebastian
core +1 more source
A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design
Advanced Intelligent Discovery, EarlyView.Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung +10 more
wiley +1 more source
Fluctuation theorem for constrained equilibrium systems
, 2006 We discuss the fluctuation properties of equilibrium chaotic systems with constraints such as isokinetic and Nosé-Hoover thermostats. Although the dynamics of these systems does not typically preserve phase-space volumes, the average phase-space ...
Gilbert, Thomas +1 more
core +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +1 more source
Fluctuation-Dissipation Theorem and Models of Learning
Neural Computation, 2005 Advances in statistical learning theory have resulted in a multitude of different designs of learning machines. But which ones are implemented by brains and other biological information processors? We analyze how various abstract Bayesian learners perform on different data and argue that it is difficult to determine which learning—theoretic computation
openaire +5 more sources
Predicting Performance of Hall Effect Ion Source Using Machine Learning
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source