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1909.04568
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BINOCULARS for Efficient, Nonmyopic Sequential Experimental Design
International Conference on Machine Learning (ICML), 2019
10 September 2019
Shali Jiang
Henry Chai
Javier I. González
Roman Garnett
OffRL
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Papers citing
"BINOCULARS for Efficient, Nonmyopic Sequential Experimental Design"
36 / 36 papers shown
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A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
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Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach
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Two-step Lookahead Bayesian Optimization with Inequality Constraints
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Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling
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Bayesian Optimization for Cascade-type Multi-stage Processes
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Shion Takeno
Yu Inatsu
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Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs
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Bing-Jing Hsieh
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Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
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Adam Foster
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GIBBON: General-purpose Information-Based Bayesian OptimisatioN
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David S. Leslie
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Paul Rayson
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Jackson Gorham
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Brian Karrer
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Bayesian Probabilistic Numerical Integration with Tree-Based Models
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Xing Liu
Ruya Kang
Zhichao Shen
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261
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ε
ε
ε
-shotgun:
ε
ε
ε
-greedy Batch Bayesian Optimisation
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Richard Everson
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293
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Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation
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A Locally Adaptive Bayesian Cubature Method
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Chris J. Oates
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