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Towards accelerating physical discovery via non-interactive and
  interactive multi-fidelity Bayesian Optimization: Current challenges and
  future opportunities

Towards accelerating physical discovery via non-interactive and interactive multi-fidelity Bayesian Optimization: Current challenges and future opportunities

20 February 2024
Arpan Biswas
Sai Mani Prudhvi Valleti
Rama K Vasudevan
M. Ziatdinov
Sergei V. Kalinin
    AI4CE
ArXivPDFHTML

Papers citing "Towards accelerating physical discovery via non-interactive and interactive multi-fidelity Bayesian Optimization: Current challenges and future opportunities"

4 / 4 papers shown
Title
Human-in-the-loop: The future of Machine Learning in Automated Electron
  Microscopy
Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy
Sergei V. Kalinin
Yongtao Liu
Arpan Biswas
Gerd Duscher
Utkarsh Pratiush
Kevin M. Roccapriore
M. Ziatdinov
Rama K Vasudevan
15
18
0
08 Oct 2023
Autonomous optimization of nonaqueous battery electrolytes via robotic
  experimentation and machine learning
Autonomous optimization of nonaqueous battery electrolytes via robotic experimentation and machine learning
Adarsh Dave
Jared M. Mitchell
S. Burke
Hongyi Lin
J. Whitacre
V. Viswanathan
46
72
0
23 Nov 2021
Autonomous Materials Discovery Driven by Gaussian Process Regression
  with Inhomogeneous Measurement Noise and Anisotropic Kernels
Autonomous Materials Discovery Driven by Gaussian Process Regression with Inhomogeneous Measurement Noise and Anisotropic Kernels
M. Noack
G. Doerk
Ruipeng Li
Jason K. Streit
R. Vaia
Kevin Yager
M. Fukuto
47
71
0
03 Jun 2020
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with
  Application to Active User Modeling and Hierarchical Reinforcement Learning
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
E. Brochu
Vlad M. Cora
Nando de Freitas
GP
131
2,447
0
12 Dec 2010
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