Search Results for author: Jiri Navratil

Found 10 papers, 2 papers with code

Learning Prediction Intervals for Model Performance

no code implementations15 Dec 2020 Benjamin Elder, Matthew Arnold, Anupama Murthi, Jiri Navratil

We address this core problem of performance prediction uncertainty with a method to compute prediction intervals for model performance.

Prediction Intervals Transfer Learning

Uncertainty Prediction for Deep Sequential Regression Using Meta Models

no code implementations2 Jul 2020 Jiri Navratil, Matthew Arnold, Benjamin Elder

Generating high quality uncertainty estimates for sequential regression, particularly deep recurrent networks, remains a challenging and open problem.

regression Uncertainty Quantification

Towards Automating the AI Operations Lifecycle

no code implementations28 Mar 2020 Matthew Arnold, Jeffrey Boston, Michael Desmond, Evelyn Duesterwald, Benjamin Elder, Anupama Murthi, Jiri Navratil, Darrell Reimer

Today's AI deployments often require significant human involvement and skill in the operational stages of the model lifecycle, including pre-release testing, monitoring, problem diagnosis and model improvements.

Accelerating Physics-Based Simulations Using Neural Network Proxies: An Application in Oil Reservoir Modeling

no code implementations23 May 2019 Jiri Navratil, Alan King, Jesus Rios, Georgios Kollias, Ruben Torrado, Andres Codas

We develop a proxy model based on deep learning methods to accelerate the simulations of oil reservoirs--by three orders of magnitude--compared to industry-strength physics-based PDE solvers.

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