Results 41 to 50 of about 2,604,808 (287)

Differentially Private Markov Chain Monte Carlo

CoRR, 2019
Recent developments in differentially private (DP) machine learning and DP Bayesian learning have enabled learning under strong privacy guarantees for the training data subjects. In this paper, we further extend the applicability of DP Bayesian learning by presenting the first general DP Markov chain Monte Carlo (MCMC) algorithm whose privacy ...
Heikkilä, Mikko, Jälkö, Joonas, Dikmen, Onur, Honkela, Antti   +3 more
openaire   +5 more sources

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Designing Vanadium‐Based Oxide Electrocatalysts for Water Splitting: Experimental and Mechanistic Insights with Machine Learning

Advanced Functional Materials, EarlyView.
This review establishes structure‐property‐mechanism relationships across six modification strategies for V‐based oxide water‐splitting electrocatalysts: lattice engineering, heteroatom doping, interface engineering, carbon‐based hybridization, morphology engineering, and surface reconstruction and pre‐catalyst design, where dissolution is reframed as ...
Youness El Issmaeli, Amina Lahrichi, Hoje Chun, Rafael Gómez‐Bombarelli, Bruno G. Pollet   +4 more
wiley   +1 more source

Application of Markov chain Monte carlo method in Bayesian statistics

MATEC Web of Conferences, 2016
In statistical inference methods, bayesian method is a method of great influence. This paper introduces the basic idea of the bayesian method. However, the widespread popularity of MCMC samplers is largely due to their impact on solving statistical ...
Zhao Qi
doaj   +1 more source

Speculative moves : multithreading Markov Chain Monte Carlo programs [PDF]

, 2008
The increasing availability of multi-core and multi-processor architectures provides new opportunities for improving the performance of many computer simulations.
Bhalerao, Abhir, Byrd, Jonathan M. R., Jarvis, Stephen A.   +2 more
core   +1 more source

Topological Spin‐Texture Transitions in van der Waals Magnets Revealed by X‐Ray Fourier Transform Holography

Advanced Materials, EarlyView.
Applied here for the first time to a 2D material, high‐resolution synchrotron x‐ray Fourier transform holography directly images topological spin textures in Fe3GeTe2. Combined with atomistic tight‐binding simulations including itinerant electrons and Rashba spin‐orbit coupling, the approach reveals labyrinth, skyrmion, and mixed phases, and uncovers ...
Sourav Chowdhury, Soumyaranjan Dash, Michael Schneider, Christopher Klose, Chithra H. Sharma, Lisa‐Marie Kern, Tim A. Butcher, Josefin Fuchs, Santanu Pakhira, Samik DuttaGupta, Takashi Taniguchi, Kenji Watanabe, Sujit Das, Sanjeev Kumar, Bastian Pfau, Amir‐Abbas Haghighirad, Moritz Hoesch   +16 more
wiley   +1 more source

Markov Chain Investigation of Discretization Schemes and Computational Cost Reduction in Modeling Photon Multiple Scattering

Applied Sciences, 2018
Establishing fast and reversible photon multiple scattering algorithms remains a modeling challenge for optical diagnostics and noise reduction purposes, especially when the scattering happens within the intermediate scattering regime.
Shangze Yang, Di Xiao, Xuesong Li, Zhen Ma   +3 more
doaj   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Enhanced Antibacterial Properties of Lyotropic Liquid Crystalline Nanoparticles via Curvature Modulation

Advanced Science, EarlyView.
Lipid nanostructured particles with increasing negative Gaussian curvature progress from vesicles to P‐cubosomes and D‐cubosomes. This curvature hierarchy enhances interaction with bacterial membranes, promotes membrane remodeling and leakage, and potentiates daptomycin activity against MRSA.
Xiangfeng Lai, Shuhong Wang, Chenguang Ding, Xenia Kostoulias, Anton P. Le Brun, Hsien‐Yi Hsu, Jhih‐Hang Jiang, Yajun Wang, Richard A. Strugnell, Anton Y. Peleg, Hsin‐Hui Shen   +10 more
wiley   +1 more source

Monte Carlo methods

EPJ Web of Conferences, 2013
Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable.
Bardenet Rémi
doaj   +1 more source