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Modified Hamiltonian Monte Carlo for Bayesian Inference
The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computational statistics. We show that performance of HMC can be significantly improved by incorporating importance sampling and ...
Opportunities at the Intersection of Synthetic Biology, Machine Learning, and Automation
Our inability to predict the behavior of biological systems severely hampers progress in bioengineering and biomedical applications. We cannot predict the effect of genotype changes on phenotype, nor extrapolate the ...
Predictive engineering and optimization of tryptophan metabolism in yeast through a combination of mechanistic and machine learning models
In combination with advanced mechanistic modeling and the generation of high-quality multi-dimensional data sets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show ...