Zobrazeno 1 - 10
of 150
pro vyhledávání: '"LEE, ROBERT M."'
Autor:
Dürholt, Johannes P., Asche, Thomas S., Kleinekorte, Johanna, Mancino-Ball, Gabriel, Schiller, Benjamin, Sung, Simon, Keupp, Julian, Osburg, Aaron, Boyne, Toby, Misener, Ruth, Eldred, Rosona, Costa, Wagner Steuer, Kappatou, Chrysoula, Lee, Robert M., Linzner, Dominik, Walz, David, Wulkow, Niklas, Shafei, Behrang
Our open-source Python package BoFire combines Bayesian Optimization (BO) with other design of experiments (DoE) strategies focusing on developing and optimizing new chemistry. Previous BO implementations, for example as they exist in the literature
Externí odkaz:
http://arxiv.org/abs/2408.05040
Autor:
Qing, Jixiang, Langdon, Becky D, Lee, Robert M, Shafei, Behrang, van der Wilk, Mark, Tsay, Calvin, Misener, Ruth
We consider the problem of optimizing initial conditions and termination time in dynamical systems governed by unknown ordinary differential equations (ODEs), where evaluating different initial conditions is costly and the state's value can not be me
Externí odkaz:
http://arxiv.org/abs/2406.02352
Robust optimisation is a well-established framework for optimising functions in the presence of uncertainty. The inherent goal of this problem is to identify a collection of inputs whose outputs are both desirable for the decision maker, whilst also
Externí odkaz:
http://arxiv.org/abs/2405.10221
The goal of multi-objective optimisation is to identify the Pareto front surface which is the set obtained by connecting the best trade-off points. Typically this surface is computed by evaluating the objectives at different points and then interpola
Externí odkaz:
http://arxiv.org/abs/2405.01404
Autor:
Folch, Jose Pablo, Tsay, Calvin, Lee, Robert M, Shafei, Behrang, Ormaniec, Weronika, Krause, Andreas, van der Wilk, Mark, Misener, Ruth, Mutný, Mojmír
Bayesian optimization is a methodology to optimize black-box functions. Traditionally, it focuses on the setting where you can arbitrarily query the search space. However, many real-life problems do not offer this flexibility; in particular, the sear
Externí odkaz:
http://arxiv.org/abs/2402.08406
Autor:
Folch, Jose Pablo, Odgers, James, Zhang, Shiqiang, Lee, Robert M, Shafei, Behrang, Walz, David, Tsay, Calvin, van der Wilk, Mark, Misener, Ruth
Publikováno v:
NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in the Real World
There has been a surge in interest in data-driven experimental design with applications to chemical engineering and drug manufacturing. Bayesian optimization (BO) has proven to be adaptable to such cases, since we can model the reactions of interest
Externí odkaz:
http://arxiv.org/abs/2312.00622
The goal of multi-objective optimisation is to identify a collection of points which describe the best possible trade-offs between the multiple objectives. In order to solve this vector-valued optimisation problem, practitioners often appeal to the u
Externí odkaz:
http://arxiv.org/abs/2305.11774
Autor:
Folch, Jose Pablo, Lee, Robert M, Shafei, Behrang, Walz, David, Tsay, Calvin, van der Wilk, Mark, Misener, Ruth
Bayesian Optimization is a useful tool for experiment design. Unfortunately, the classical, sequential setting of Bayesian Optimization does not translate well into laboratory experiments, for instance battery design, where measurements may come from
Externí odkaz:
http://arxiv.org/abs/2211.06149
Autor:
Thebelt, Alexander, Tsay, Calvin, Lee, Robert M., Sudermann-Merx, Nathan, Walz, David, Shafei, Behrang, Misener, Ruth
Tree ensembles can be well-suited for black-box optimization tasks such as algorithm tuning and neural architecture search, as they achieve good predictive performance with little or no manual tuning, naturally handle discrete feature spaces, and are
Externí odkaz:
http://arxiv.org/abs/2207.00879
Autor:
Folch, Jose Pablo, Zhang, Shiqiang, Lee, Robert M, Shafei, Behrang, Walz, David, Tsay, Calvin, van der Wilk, Mark, Misener, Ruth
Bayesian Optimization is a very effective tool for optimizing expensive black-box functions. Inspired by applications developing and characterizing reaction chemistry using droplet microfluidic reactors, we consider a novel setting where the expense
Externí odkaz:
http://arxiv.org/abs/2202.00060