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09/12/2023
Identifying Bayesian Optimal Experiments for Uncertain Biochemical Pathway Models
Pharmacodynamic (PD) models are mathematical models of cellular reaction...
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09/06/2023
Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks
Bayesian inference for neural networks, or Bayesian deep learning, has t...
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06/14/2023
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators
Modern climate projections lack adequate spatial and temporal resolution...
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04/27/2020