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Found 9 papers, 0 papers with code
Variational Exploration Module VEM: A Cloud-Native Optimization and Validation Tool for Geospatial Modeling and AI Workflows
Geospatial observations combined with computational models have become key to understanding the physical systems of our environment and enable the design of best practices to reduce societal harm.
Learning to Act: Novel Integration of Algorithms and Models for Epidemic Preparedness
In this work we present a framework which may transform research and praxis in epidemic planning.
A Collaborative Approach to the Analysis of the COVID-19 Response in Africa
The COVID-19 crisis has emphasized the need for scientific methods such as machine learning to speed up the discovery of solutions to the pandemic.
Surrogate Ensemble Forecasting for Dynamic Climate Impact Models
Seasonal ensembles forecasts of temperature and precipitation with a 6-month horizon are propagated through the model, predicting the distribution of transmission time series.
Deep Temporal Interpolation of Radar-based Precipitation
When providing the boundary conditions for hydrological flood models and estimating the associated risk, interpolating precipitation at very high temporal resolutions (e. g. 5 minutes) is essential not to miss the cause of flooding in local regions.
Trusted Multi-Party Computation and Verifiable Simulations: A Scalable Blockchain Approach
Large-scale computational experiments, often running over weeks and over large datasets, are used extensively in fields such as epidemiology, meteorology, computational biology, and healthcare to understand phenomena, and design high-stakes policies affecting everyday health and economy.
Characterizing the hyper-parameter space of LSTM language models for mixed context applications
Applying state of the art deep learning models to novel real world datasets gives a practical evaluation of the generalizability of these models.
Novel Exploration Techniques (NETs) for Malaria Policy Interventions
The task of decision-making under uncertainty is daunting, especially for problems which have significant complexity.
Using Genetic Algorithms to Benchmark the Cloud
Results also show the effectiveness of our GA in determining the level of service of PaaS providers, and for determining if the level of service of one PaaS vendor is repeatable with another.
