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High dimensional gradient-augmented Bayesian optimization with adjoint solvers
Combinatorial Bayesian Optimisation with Applications to Antibody discovery and Logic Synthesis EDA
Bayesian Optimization (Bayes Opt): Easy explanation of popular hyperparameter tuning method
Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces, S. Daulton, et al
Pre-trained Ensembles for Bayesian Optimization of Protein Sequences | Ziyue Yang
Roman Garnett - Bayesian Optimization
2021 3.3 Data efficient Optimization with Bayesian Optimization - Roberto Calandra
SCITalk: Bayesian optimization and design of experiments
[AutoMLConf'22]: Are we forgetting about compositional optimisers in Bayesian optimisation
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Last Updated: September 6, 2026
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Summary
Abstract: Scientists and engineers in diverse domains need to perform expensive experiments to If you enjoyed this talk, consider joining the Molecular Modeling and Drug Discovery (M2D2) talks live: ... A short and simple summary of: * We combine adjoint solvers with gradient-augmented REALML Online reading group realworldml.github.io/ Abstract: Many critical emerging real-world problems are instances of ... by Swaraj Vatsa for ANC Journal Club. Title: Understanding High-Dimensional The talk by Roman Garnett at the Probabilistic Numerics Spring School 2023 in Tübingen, Professor Ruth Misener is the BASF/RAEng Research Chair in Data-Driven The Paper can be read here: jmlr.org/papers/volume22/20-1422/20-1422.pdf.
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