Field dossier · from the corpus
Bayesian optimization
0predicted collisions
Where this field is predicted to collide
No open collisions on this field in the current run.
Most cited work
On-the-fly closed-loop materials discovery via Bayesian active learning
LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes
Bayesian Machine Learning in Metamaterial Design: Fragile Becomes Supercompressible
Two-step machine learning enables optimized nanoparticle synthesis
Machine learning-driven materials discovery: Unlocking next-generation functional materials – A review
An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics
Recent work · 2024 onward
Machine learning-driven materials discovery: Unlocking next-generation functional materials – A review
Active learning accelerates the discovery of high strength and high ductility lead-free solder alloys
Microstructure-aware Bayesian materials design
Computational intelligence approaches for hydrogen storage material design
A review of simulation, characterization, and informatics in inorganic materials
Density-aware active learning for materials discovery: a case study on functionalized nanoporous materials