Results 161 to 170 of about 43,032 (264)
Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford +3 more
wiley +1 more source
The recognition method of external force damage sources vibration signals based on LSTM-CNN-CatBoost-GSSSA. [PDF]
Chen X, Zhang L, Li X, Gao F.
europepmc +1 more source
Enhancing Super‐Resolution Spatial Transcriptomics Data by Transfer Learning
SpotZoomer employs a transfer‐learning‐based strategy to enhance the resolution of Visium data by leveraging available high‐resolution priors. The resulting super‐resolved maps enable sharper delineation of cell boundaries and more precise inference of cell–cell communication patterns that would otherwise remain obscured at native resolution.
Xiaoyu Li, Lihua Zhang, Wenwen Min
wiley +1 more source
A CCO-PPO Framework for Autonomous UAV Trajectory Tracking in Complex and Disturbed Environments. [PDF]
Guo X +6 more
europepmc +1 more source
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park +3 more
wiley +1 more source
Metaheuristic optimization of deep CNNs for multi-class diagnosis of cervical cancer and lymphoma. [PDF]
Abdelhay EH, Elgamily KM, Badr WOE.
europepmc +1 more source
Machine learning‐guided strain engineering enables highly active, durable, support‐free Pt–Ni nanonetwork catalysts for the oxygen reduction reaction. Analysis of a Pt‐based catalyst dataset identifies surface compressive strain as an effective descriptor associated with enhanced activity and provided practical design guidelines.
Aparna Chitra Sudheer +4 more
wiley +1 more source
Empirical Bayes Covariance Decomposition, and a Solution to the Multiple Tuning Problem in Sparse PCA. [PDF]
Kang J, Stephens M.
europepmc +1 more source
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley +1 more source

