Results 111 to 120 of about 19,980 (297)
Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors
AIChE Journal, EarlyView.Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley +1 more source
A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization [PDF]
, 2016 In this paper, we suggest a new nonlinear conjugate gradient method for solving large scale unconstrained optimization problems. We prove that the new conjugate gradient coefficient βk with exact line search is globally convergent.
Zabidin Salleh (2796652) +3 more
core +1 more source
Unbiased Structure Prediction of Sophisticated Cage Structures
Angewandte Chemie, EarlyView.We introduce the software and workflow for automated, unbiased exploration of all possible connectivities of a given set of building blocks and their stoichiometry to predict stable cage structures. ABSTRACT Cage structure prediction has made significant strides by generating structures based on what the community has seen before.
Andrew Tarzia, Giovanni M. Pavan
wiley +2 more sources
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
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
Advanced Intelligent Discovery, EarlyView.Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley +1 more source
Comparison of response surface methodology and the Nelder and Mead simplex method for optimization in microsimulation models [PDF]
Microsimulation models are increasingly used in the evaluation of cancer screening. Latent parameters of such models can be estimated by optimization of the goodness-of-fit.
Neddermeijer, H.G. +4 more
core +1 more source
MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design
Advanced Intelligent Discovery, EarlyView.MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa +2 more
wiley +1 more source
A contribution to theory and practice of nonlinear parameter optimization [PDF]
, 1975 Nonlinear parameter optimization in least squares was studied from a point of view of differential geometry. Properties of curvilinear coordinates, scale factors and curvature were investigated.
Stol, P.T.
core
Advanced Intelligent Systems, EarlyView.A quadrupedal integrated leg‐arm robot with an underactuated reconfigurable body is developed. By using a Sarrus mechanism as the body, the robot enables reconfiguration through its supporting limbs, achieving mode switching without additional actuators.
Xinghan Zhuang +8 more
wiley +1 more source