Results 171 to 180 of about 56,129 (265)

Failure-avoidance bayesian optimization with failure-boundary search for automatic exploration of digging control parameters. [PDF]

Sci Rep
Koyama M, Ishikawa M.
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Bayesian Optimization for Multicomponent Supramolecular Systems. [PDF]

J Am Chem Soc
Jansen SAH, Markvoort AJ, Graaf FV, Rutten MGTA, Dankers PYW, Vantomme G, de Greef TFA, Meijer EW.   +7 more
europepmc   +1 more source

The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers

Advanced Intelligent Discovery, EarlyView.
We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen, Patrick W. V. Butler, Jesper R. Pedersen, Nis Fisker‐Bødker, Tejs Vegge, Jin Hyun Chang, Ivano E. Castelli   +6 more
wiley   +1 more source

Experiment-Driven Gaussian Process Surrogate Modeling and Bayesian Optimization for Multi-Objective Injection Molding. [PDF]

Polymers (Basel)
Omar HM, Mukras SMS.
europepmc   +1 more source

Imprecise Bayesian optimization

Knowledge-Based Systems
Julian Rodemann, Thomas Augustin 0001
openaire   +2 more sources

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

Validation of Dynamic Bayesian Optimization for a Non-Stationary Human-in-the-Loop Optimization Problem. [PDF]

IEEE Robot Autom Lett
Kim G, Sergi F.
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Accelerated discovery of highly active enzyme nanohybrids with parallelized Bayesian optimization in hybrid space. [PDF]

Nat Commun
Liu Y, Hu H, Han Y, Deon Chon JS, Lo CL, Chen Z, Zhang Z, Yuan Z, Ge J.   +8 more
europepmc   +1 more source