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pro vyhledávání: '"Miller,John"'
A critical bottleneck for scientific progress is the costly nature of computer simulations for complex systems. Surrogate models provide an appealing solution: such models are trained on simulator evaluations, then used to emulate and quantify uncert
Externí odkaz:
http://arxiv.org/abs/2410.12690
Autor:
Miller, John Joshua, Mak, Simon, Sun, Benny, Narayanan, Sai Ranjeet, Yang, Suo, Sun, Zongxuan, Kim, Kenneth S., Kweon, Chol-Bum Mike
The optimization of expensive black-box simulators arises in a myriad of modern scientific and engineering applications. Bayesian optimization provides an appealing solution, by leveraging a fitted surrogate model to guide the selection of subsequent
Externí odkaz:
http://arxiv.org/abs/2410.01196
Autor:
Huang, Tianshu, Miller, John, Prabhakara, Akarsh, Jin, Tao, Laroia, Tarana, Kolter, Zico, Rowe, Anthony
Simulation is an invaluable tool for radio-frequency system designers that enables rapid prototyping of various algorithms for imaging, target detection, classification, and tracking. However, simulating realistic radar scans is a challenging task th
Externí odkaz:
http://arxiv.org/abs/2403.03896
Autor:
Miller, John Joshua, Mak, Simon
The optimization of a black-box simulator over control parameters $\mathbf{x}$ arises in a myriad of scientific applications. In such applications, the simulator often takes the form $f(\mathbf{x},\boldsymbol{\theta})$, where $\boldsymbol{\theta}$ ar
Externí odkaz:
http://arxiv.org/abs/2403.03816
Accelerated sea level rise has resulted in recurrent flooding in coastal regions, increasingly impacting both transportation systems and local populations. Using the Hampton Roads region in Virginia as a case study, this study a. identifies hotspots
Externí odkaz:
http://arxiv.org/abs/2402.07959