Results 201 to 210 of about 456,013 (364)

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Optimal Transfer of Entanglement in Oscillator Chains in Non-Markovian Open Systems. [PDF]

Entropy (Basel)
Luo DW, Yu E, Yu T.
europepmc   +1 more source

The stability of a quadratic type functional equation with the fixed point alternative [PDF]

, 2008
M‎. ‎Eshaghi Gordji, H. Khodaei
openalex   +1 more source

Accelerating Surface Composition Characterization of Thin‐Film Materials Libraries Using Multi‐Output Gaussian Process Regression

Advanced Intelligent Discovery, EarlyView.
To integrate surface analysis into materials discovery workflows, Gaussian process regression is used to accurately predict surface compositions from rapidly acquired volume composition data (obtained by energy‐dispersive X‐ray spectroscopy), drastically reducing the number of required surface measurements on thin‐film materials libraries.
Felix Thelen, Florian Lourens, Alfred Ludwig   +2 more
wiley   +1 more source

Green's Function Perspective on the Nonlinear Density Response of Quantum Many-Body Systems. [PDF]

J Stat Phys
Vorberger J, Dornheim T, Böhme MP, Moldabekov ZA, Tolias P.   +4 more
europepmc   +1 more source

Stability of Quadratic Functional Equations [PDF]

, 2011
openaire   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Optimization of Sweet Leaf (<i>Sauropus androgynus</i> L. Merr)-Amaranth (<i>Amaranthus hybridus</i> L.) Vegetable Leather With Carrageenan and Sorbitol. [PDF]

Scientifica (Cairo)
Purwoto H, Purnamasari AP, Rusbana TB, Nurtiana W, Putri RPG, Soraya M, Laksono H.   +6 more
europepmc   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

Effect of ammonium hydroxide modification of ZIF-8 nanoparticles on hexavalent chromium removal from aqueous solution. [PDF]

Sci Rep
Rakshitha KM, Giridhar R, Prathima B, Sainath K.   +3 more
europepmc   +1 more source