308 citations
- Duke UniversityUS58 papers
- University of North Carolina at Chapel HillUS13 papers
- North Carolina State UniversityUS11 papers
- University of California, BerkeleyUS7 papers
- Statistical Research (United States)US5 papers
- Texas A&M UniversityUS5 papers
- University of CincinnatiUS5 papers
- Clarkson UniversityUS4 papers
- Department of Mathematical SciencesRU4 papers
- Harvard UniversityUS4 papers
- University of WashingtonUS4 papers
- Cornell UniversityUS3 papers
4 papers · 1 filter
Random forest model identifies serve strength as a key predictor of tennis match outcome
Zijian Gao, Amanda Kowalczyk
Tennis is a popular sport worldwide, boasting millions of fans and numerous national and international tournaments. Like many sports, tennis has benefitted from the popularity of r…
Analyzing Collective Motion with Machine Learning and Topology
Dhananjay Bhaskar, Angelika Manhart, Jesse Milzman +4
We use topological data analysis and machine learning to study a seminal model of collective motion in biology [D'Orsogna et al., Phys. Rev. Lett. 96 (2006)]. This model describes…
Learning partial differential equations for biological transport models from noisy spatiotemporal data
John Lagergren, John T. Nardini, G. Michael Lavigne +2
We investigate methods for learning partial differential equation (PDE) models from spatiotemporal data under biologically realistic levels and forms of noise. Recent progress in l…
Estimating population average treatment effects from experiments with noncompliance
Kellie Ottoboni, Jason Poulos
Randomized control trials (RCTs) are the gold standard for estimating causal effects, but often use samples that are non-representative of the actual population of interest. We pro…