Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection ...

A paper co-authored by Prof. Alex Lew has been selected as one of four "Outstanding Papers" at this year's Conference on Language Modeling (COLM 2025), held in Montreal in October.

In this video from FOSDEM 2020, Frank McQuillan from Pivotal presents: Efficient Model Selection for Deep Neural Networks on Massively Parallel Processing Databases. In this session we will present an ...

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.

Although several flow routing (FR) algorithms are developed for hydrological modeling, it is still uncertain how the selection of algorithms may affect model results. This study aims to explore the ...

We consider problems in model selection caused by the geometry of models close to their points of intersection. In some cases—including common classes of causal or graphical models, as well as time ...

Machine learning algorithms are used everywhere from a smartphone to a spacecraft. They tell you the weather forecast for tomorrow, translate from one language into another, and suggest what TV series ...