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GPdoemd: A Python package for design of experiments for model discrimination
16 references·0 citing·42 second hop
GPdoemd: A Python package for design of experiments for model discrimination (2019)GPdoemd: A Python package for design of e…When Quality Beats Quantity: Decision Theory, Drug Discovery, and the Reproducibility Crisis (2016)When Quality Beats Quantity: …Innovation in the pharmaceutical industry: New estimates of R&D costs (2016)Innovation in the pharmaceuti…Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)Taking the Human Out of the L…Batch Bayesian Optimization via Local Penalization (2015)Batch Bayesian Optimization v…A Review of Modern Computational Algorithms for Bayesian Optimal Design (2015)A Review of Modern Computatio…Design of Dynamic Experiments: A Data-Driven Methodology for the Optimization of Time-Varying Processes (2013)Design of Dynamic Experiments…Model-Based Design of Parallel Experiments (2007)Model-Based Design of Paralle…DT-optimum designs for model discrimination and parameter estimation (2007)DT-optimum designs for model …A new approach for sequential experimental design for model discrimination (2006)A new approach for sequential…An improved version of a sequential design criterion for discriminating among rival multiresponse models (1990)An improved version of a sequ…The optimal design of dynamic experiments (1989)The optimal design of dynamic…Sequential experimental design for model discrimination in the case of multiple responses (1984)Sequential experimental desig…A new sequential experimental design procedure for discriminating among rival models (1983)A new sequential experimental…The Design of Experiments for Discriminating Between two Rival Models (1975)The Design of Experiments for…Discrimination Among Mechanistic Models (1967)Discrimination Among Mechanis…Designs for Discriminating Between Two Rival Models (1965)Designs for Discriminating Be…Optimum Designs in Regression Problems (1959)Optimum Experimental Designs (1992)Optimal design of experiments (1993)Model-based design of experiments for parameter precision: State of the art (2007)Novel anticorrelation criteria for model‐based experiment design: Theory and formulations (2008)Online Model-Based Redesign of Experiments for Parameter Estimation in Dynamic Systems (2009)On the Experimental Attainment of Optimum Conditions (1951)Design and Analysis of Industrial Experiments. (1955)Designing Environmental Field Studies (1991)On the Experimental Attainment of Optimum Conditions (1992)9 Computer experiments (1996)DESIGN OF EXPERIMENTS IN NON-LINEAR SITUATIONS (1959)A Stochastic Approximation Method (1951)Theory of optimal experiments (1972)Theory of Optimal Experiments. (1972)Bayesian Design of Experiments Using Approximate Coordinate Exchange (2016)Forecasting carbon price trends based on an interpretable light gradient boosting machine and Bayesian optimization (2023)Modern Bayesian Experimental Design (2024)Design and Analysis of Computer Experiments (1989)Prediction, Learning, and Games (2006)Practical Bayesian Optimization of Machine Learning Algorithms (2012)A Tutorial on Bayesian Optimization (2018)Bayesian Optimization (2018)BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization (2019)Construct validity in psychological tests. (1955)Why Most Published Research Findings Are False (2005)Power failure: why small sample size undermines the reliability of neuroscience (2013)US Pharma's Financialized Business Model (2017)Financialized Corporations in a National Innovation System: The U.S. Pharmaceutical Industry (2018)Analysis of pharma R&D productivity – a new perspective needed (2023)Cost-Effectiveness in Health and Medicine (1996)The price of innovation: new estimates of drug development costs (2003)How to improve R&D productivity: the pharmaceutical industry's grand challenge (2010)Essential medicines for universal health coverage (2016)The High Cost of Prescription Drugs in the United States (2016)Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018 (2020)Self-optimisation and model-based design of experiments for developing a C–H activation flow process (2017)Experimental Design: Review and Comment (1984)Response Surface Methodology: 1966-1988 (1989)Systems biology: experimental design (2009)Scalable Global Optimization via Local Bayesian Optimization (2019)Bayesian Optimization for Adaptive Experimental Design: A Review (2020)
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References

  • 2015Taking the Human Out of the Loop: A Review of Bayesian Optimization6,203 cited
  • 2016Innovation in the pharmaceutical industry: New estimates of R&D costs3,621 cited
  • 1967Discrimination Among Mechanistic Models428 cited
  • 2015A Review of Modern Computational Algorithms for Bayesian Optimal Design339 cited
  • 1975The Design of Experiments for Discriminating Between two Rival Models301 cited
  • 2016When Quality Beats Quantity: Decision Theory, Drug Discovery, and the Reproducibility Crisis279 cited
  • 2015Batch Bayesian Optimization via Local Penalization212 cited
  • 1965Designs for Discriminating Between Two Rival Models210 cited
  • 2007Model-Based Design of Parallel Experiments107 cited
  • 1989The optimal design of dynamic experiments107 cited
  • 2007DT-optimum designs for model discrimination and parameter estimation90 cited
  • 1983A new sequential experimental design procedure for discriminating among rival models84 cited
  • 1984Sequential experimental design for model discrimination in the case of multiple responses78 cited
  • 2013Design of Dynamic Experiments: A Data-Driven Methodology for the Optimization of Time-Varying Processes77 cited
  • 2006A new approach for sequential experimental design for model discrimination

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62 cited
  • 1990An improved version of a sequential design criterion for discriminating among rival multiresponse models52 cited
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