4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 2 cited
Towards Stability of Autoregressive Neural Operators
Michael McCabe, Peter Harrington, Shashank Subramanian +1
Neural operators have proven to be a promising approach for modeling spatiotemporal systems in the physical sciences. However, training these models for large systems can be quite…
cs.LG2021★ 4 cited
Learning to Assimilate in Chaotic Dynamical Systems
Michael McCabe, Jed Brown
The accuracy of simulation-based forecasting in chaotic systems is heavily dependent on high-quality estimates of the system state at the time the forecast is initialized. Data ass…
cs.CG2018★ 1 cited
Mapper Comparison with Wasserstein Metrics
Michael McCabe
The challenge of describing model drift is an open question in unsupervised learning. It can be difficult to evaluate at what point an unsupervised model has deviated beyond what w…