Results 271 to 280 of about 616,883 (325)

Measuring Statistical Dependence via Characteristic Function IPM. [PDF]

Entropy (Basel)
Daniušis P, Juneja S, Kuzma L, Marcinkevičius V.   +3 more
europepmc   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Ramifications of generalized Feller theory. [PDF]

J Evol Equ
Cuchiero C, Möllmann T, Teichmann J.
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

Power-Law Reliability Plotting for Microelectronics. [PDF]

Micromachines (Basel)
Bernstein JB.
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Deriving national and disaggregated estimates for the demand for family planning satisfied indicator from contraceptive prevalence using household health surveys. [PDF]

Reprod Health
Ferreira LZ, Hellwig F, Lima NP, Barros AJD.   +3 more
europepmc   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Temperature Hysteresis Calibration Method of MEMS Accelerometer. [PDF]

Sensors (Basel)
Kim HJ, Jung HK.
europepmc   +1 more source

"Gold-Standard" Δ-Machine Learned Transferable Potential for Linear Alkanes. [PDF]

J Phys Chem Lett
Qu C, Nandi A, Houston PL, Yu Q, Conte R, Bowman JM.   +5 more
europepmc   +1 more source