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Found 7 papers, 4 papers with code
On the calibration of compartmental epidemiological models
Finally, we discuss how the calibration of parameters of epidemiological compartmental models is an emerging field that has the potential to improve the accuracy of disease modeling and public health decision-making.
Planning Multiple Epidemic Interventions with Reinforcement Learning
We illustrate how to effectively apply state-of-the-art actor-critic reinforcement learning algorithms (PPO and SAC) to search for plans that minimize overall costs.
Forgetful Forests: high performance learning data structures for streaming data under concept drift
The forgetful algorithms described in this paper achieve high time performance while maintaining high quality predictions on streaming data.
Classification Under Ambiguity: When Is Average-K Better Than Top-K?
This paper formally characterizes the ambiguity profile when average-$K$ classification can achieve a lower error rate than a fixed top-$K$ classification.
Robotic Room Traversal using Optical Range Finding
Our room traversal algorithm relies upon the approximate distance from the robot to the nearest obstacle in 360 degrees.
Debugging Machine Learning Pipelines
Machine learning tasks entail the use of complex computational pipelines to reach quantitative and qualitative conclusions.
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
To review progress in the field, the analysis also compared the best methods participating in CAFA1 to those of CAFA2.
Quantitative Methods
