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Bayesian optimization (BO) is a popular approach for sample-efficient optimization of black-box objective functions.
Robust model-free reinforcement learning with multi-objective bayesian optimization, 2019
M. Turchetta, A. Krause, and S. Trimpe · 1910
Earlier work this paper cites.
On bayesian methods for seeking the extremum
J. Močkus · 1975
Earlier work this paper cites.
Efficient global optimization of expensive black-box functions
D. R. Jones, M. Schonlau, and W. J. Welch · 1998
Earlier work this paper cites.
Gaussian processes in machine learning
C. E. Rasmussen · 2003
Earlier work this paper cites.
Bop-elites, a bayesian optimisation algorithm for quality-diversity search, 2020
P. Kent and J. Branke · 2005
Earlier work this paper cites.
A stochastic radial basis function method for the global optimization of expensive functions
R. G. Regis and C. A. Shoemaker · 2007
Earlier work this paper cites.
Variational learning of inducing variables in sparse gaussian processes
M. Titsias · 2009
Earlier work this paper cites.
The knowledge-gradient algorithm for sequencing experiments in drug discovery
D. M. Negoescu, P. I. Frazier, and W. B. Powell · 2011
Earlier work this paper cites.
Gaussian processes for big data
J. Hensman, N. Fusi, and N. D. Lawrence · 2013
Earlier work this paper cites.
Bayesian optimization with inequality constraints
J. R. Gardner, M. J. Kusner, Z. E. Xu, K. Q. Weinberger, and J. P. Cunningham · 2014
Earlier work this paper cites.
Predictive entropy search for multi-objective bayesian optimization, 2015
D. Hernández-Lobato, J. M. Hernández-Lobato, A. Shah, and R. P. Adams · 2015
Earlier work this paper cites.
High dimensional Bayesian optimisation and bandits via additive models
K. Kandasamy, J. Schneider, and B. Póczos · 2015
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Illuminating search spaces by mapping elites, 2015
J.-B. Mouret and J. Clune · 2015
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Taking the human out of the loop: A review of Bayesian optimization
B. Shahriari, K. Swersky, Z. Wang, R. P. Adams, and N. De Freitas · 2015
Earlier work this paper cites.
Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases
K. Williams, E. Bilsland, A. Sparkes, W. Aubrey, M. Young, L. N. Soldatova, K. De Grave, J. Ramon, M. de Clare, W. Sirawaraporn, S. G. Oliver, and R. D. King · 2015
Earlier work this paper cites.
The cma evolution strategy: A tutorial, 2016
N. Hansen · 2016
Earlier work this paper cites.
Using centroidal voronoi tessellations to scale up the multi-dimensional archive of phenotypic elites algorithm, 2016
V. Vassiliades, K. Chatzilygeroudis, and J.-B. Mouret · 2016
Earlier work this paper cites.
Bayesian optimization in a billion dimensions via random embeddings
Z. Wang, F. Hutter, M. Zoghi, D. Matheson, and N. De Freitas · 2016
Earlier work this paper cites.
Parallel and distributed Thompson sampling for large-scale accelerated exploration of chemical space
J. M. Hernández-Lobato, J. Requeima, E. O. Pyzer-Knapp, and A. Aspuru-Guzik · 2017
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The true destination of ego is multi-local optimization, 2017
S. Wessing and M. Preuss · 2017
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Bayesian optimization and attribute adjustment
S. Eissman, D. Levy, R. Shu, S. Bartzsch, and S. Ermon · 2018
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A tutorial on Bayesian optimization
P. I. Frazier · 2018
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Data-efficient design exploration through surrogate-assisted illumination
A. Gaier, A. Asteroth, and J.-B. Mouret · 2018
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Zinc20—a free ultralarge-scale chemical database for ligand discovery
J. J. Irwin, K. G. Tang, J. Young, C. Dandarchuluun, B. R. Wong, M. Khurelbaatar, Y. S. Moroz, J. Mayfield, and R. A. Sayle · 2020
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Parametric gaussian process regressors
M. Jankowiak, G. Pleiss, and J. R. Gardner · 2020
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Diversity-guided multi-objective bayesian optimization with batch evaluations
M. Konakovic Lukovic, Y. Tian, and W. Matusik · 2020
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Re-examining linear embeddings for high-dimensional Bayesian optimization
B. Letham, R. Calandra, A. Rai, and E. Bakshy · 2020
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Quality diversity for multi-task optimization
J.-B. Mouret and G. Maguire · 2020
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A survey of trajectory distance measures and performance evaluation
H. Su, S. Liu, B. Zheng, X. Zhou, and K. Zheng · 2020
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J. R. Gardner, G. Pleiss, D. Bindel, K. Q. Weinberger, and A. G. Wilson · 2018
Cited alongside, same era.
Automatic chemical design using a data-driven continuous representation of molecules
R. Gómez-Bombarelli, J. N. Wei, D. Duvenaud, J. M. Hernández-Lobato, B. Sánchez-Lengeling, D. Sheberla, J. Aguilera-Iparraguirre, T. D. Hirzel, R. P. Adams, and A. Aspuru-Guzik · 2018
Cited alongside, same era.
Junction tree variational autoencoder for molecular graph generation
W. Jin, R. Barzilay, and T. S. Jaakkola · 2018
Cited alongside, same era.
Efficient high dimensional Bayesian optimization with additivity and quadrature Fourier features
M. Mutny and A. Krause · 2018
Cited alongside, same era.
Batched large-scale Bayesian optimization in high-dimensional spaces
Z. Wang, C. Gehring, P. Kohli, and S. Jegelka · 2018
Cited alongside, same era.
Max-value entropy search for multi-objective bayesian optimization
S. Belakaria, A. Deshwal, and J. R. Doppa · 2019
Cited alongside, same era.
Guacamol: Benchmarking models for de novo molecular design
N. Brown, M. Fiscato, M. H. Segler, and A. C. Vaucher · 2019
Cited alongside, same era.
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Sample-efficient optimization in the latent space of deep generative models via weighted retraining
A. Tripp, E. A. Daxberger, and J. M. Hernández-Lobato · 2020
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Multi-objective bayesian optimization over high-dimensional search spaces
S. Daulton, D. Eriksson, M. Balandat, and E. Bakshy · 2021
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Scalable constrained Bayesian optimization
D. Eriksson and M. Poloczek · 2021
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Accelerating high-throughput virtual screening through molecular pool-based active learning
D. E. Graff, E. I. Shakhnovich, and C. W. Coley · 2021
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High-dimensional Bayesian optimisation with variational autoencoders and deep metric learning
A. Grosnit, R. Tutunov, A. M. Maraval, R. Griffiths, A. I. Cowen-Rivers, L. Yang, L. Zhu, W. Lyu, Z. Chen, J. Wang, J. Peters, and H. Bou-Ammar · 2021
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Bayesian algorithm execution: Estimating computable properties of black-box functions using mutual information
W. Neiswanger, K. A. Wang, and S. Ermon · 2021
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Good practices for Bayesian optimization of high dimensional structured spaces
E. Siivola, A. Paleyes, J. González, and A. Vehtari · 2021
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Bayesian optimization is superior to random search for machine learning hyperparameter tuning: Analysis of the black-box optimization challenge 2020
R. Turner, D. Eriksson, M. McCourt, J. Kiili, E. Laaksonen, Z. Xu, and I. Guyon · 2021
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Y. Xie, Z. Xu, J. Ma, and Q. Mei · 2021
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Local latent space bayesian optimization over structured inputs
N. Maus, H. T. Jones, J. S. Moore, M. J. Kusner, J. Bradshaw, and J. R. Gardner · 2022
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Accelerating bayesian optimization for biological sequence design with denoising autoencoders, 2022
S. Stanton, W. Maddox, N. Gruver, P. Maffettone, E. Delaney, P. Greenside, and A. G. Wilson · 2022
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