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Bayesian optimization offers a sample-efficient framework for navigating the exploration-exploitation trade-off in the vast design space of biological sequences.
On bayesian methods for seeking the extremum
Jonas Močkus · 1975
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Efficient global optimization of expensive black-box functions
Donald R Jones, Matthias Schonlau, and William J Welch · 1998
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Single-and multi-objective evolutionary design optimization assisted by gaussian random field metamodels
Michael Emmerich · 2005
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Gaussian processes for machine learning (adaptive computation and machine learning), 2005
CE Rasmussen and CKI Williams · 2005
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Novel trends in high-throughput screening
Lorenz M Mayr and Dejan Bojanic · 2009
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Kriging is well-suited to parallelize optimization
David Ginsbourger, Rodolphe Le Riche, and Laurent Carraro · 2010
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Hypervolume-based expected improvement: Monotonicity properties and exact computation
Michael TM Emmerich, André H Deutz, and Jan Willem Klinkenberg · 2011
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Bayesian optimization with unknown constraints
Michael A Gelbart, Jasper Snoek, and Ryan P Adams · 2014
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Bayesian optimization with inequality constraints
Jacob R Gardner, Matt J Kusner, Zhixiang Eddie Xu, Kilian Q Weinberger, and John P Cunningham · 2014
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Validation of noise models for single-cell transcriptomics
Dominic Grün, Lennart Kester, and Alexander Van Oudenaarden · 2014
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Developability assessment during the selection of novel therapeutic antibodies
Alexander Jarasch, Hans Koll, Joerg T Regula, Martin Bader, Apollon Papadimitriou, and Hubert Kettenberger · 2015
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Taking the human out of the loop: A review of bayesian optimization
Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P Adams, and Nando De Freitas · 2015
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On statistical methods for zero-inflated models, 2015
Julia Eggers · 2015
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The parallel knowledge gradient method for batch bayesian optimization
Jian Wu and Peter Frazier · 2016
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A general framework for constrained bayesian optimization using information-based search
José Miguel Hernández-Lobato, Michael A Gelbart, Ryan P Adams, Matthew W Hoffman, and Zoubin Ghahramani · 2016
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Biophysical properties of the clinical-stage antibody landscape
Tushar Jain, Tingwan Sun, Stéphanie Durand, Amy Hall, Nga Rewa Houston, Juergen H Nett, Beth Sharkey, Beata Bobrowicz, Isabelle Caffry, Yao Yu, et al · 2017
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Bayesian optimization for accelerated drug discovery
Differentiable expected hypervolume improvement for parallel multi-objective bayesian optimization
Samuel Daulton, Maximilian Balandat, and Eytan Bakshy · 2020
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Low-n protein engineering with data-efficient deep learning
Surojit Biswas, Grigory Khimulya, Ethan C Alley, Kevin M Esvelt, and George M Church · 2021
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Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations
Payel Das, Tom Sercu, Kahini Wadhawan, Inkit Padhi, Sebastian Gehrmann, Flaviu Cipcigan, Vijil Chenthamarakshan, Hendrik Strobelt, Cicero Dos Santos, Pin-Yu Chen, et al · 2021
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Function-guided protein design by deep manifold sampling
Vladimir Gligorijevic, Daniel Berenberg, Stephen Ra, Andrew Watkins, Simon Kelow, Kyunghyun Cho, and Richard Bonneau · 2021
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Parallel bayesian optimization of multiple noisy objectives with expected hypervolume improvement
Samuel Daulton, Maximilian Balandat, and Eytan Bakshy · 2021
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Edward O Pyzer-Knapp · 2018
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A tutorial on bayesian optimization
Peter I Frazier · 2018
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Bayesian optimization for multi-objective optimization and multi-point search
Takashi Wada and Hideitsu Hino · 2019
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A multi-point mechanism of expected hypervolume improvement for parallel multi-objective bayesian global optimization
Kaifeng Yang, Pramudita Satria Palar, Michael Emmerich, Koji Shimoyama, and Thomas Bäck · 2019
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Constrained bayesian optimization with noisy experiments
Benjamin Letham, Brian Karrer, Guilherme Ottoni, and Eytan Bakshy · 2019
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A primer on model-guided exploration of fitness landscapes for biological sequence design
Sam Sinai and Eric D Kelsic · 2020
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Bayesian optimization of function networks
Raul Astudillo and Peter Frazier · 2021
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Beyond the pareto efficient frontier: Constraint active search for multiobjective experimental design
Gustavo Malkomes, Bolong Cheng, Eric H Lee, and Mike Mccourt · 2021
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Scalable bayesian optimization accelerates process optimization of penicillin production
Qiaohao Liang and Lipeng Lai · 2021
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Batched bayesian optimization for drug design in noisy environments
Hugo Bellamy, Abbi Abdel Rehim, Oghenejokpeme I Orhobor, and Ross King · 2022
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Accelerating bayesian optimization for biological sequence design with denoising autoencoders
Samuel Stanton, Wesley Maddox, Nate Gruver, Phillip Maffettone, Emily Delaney, Peyton Greenside, and Andrew Gordon Wilson · 2022
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Bayesian optimization over discrete and mixed spaces via probabilistic reparameterization
Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A Osborne, and Eytan Bakshy · 2022
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