7 papers
Knowledge-Guided Machine Learning: Illustrating the use of Explainable Boosting Machines to Identify Overshooting Tops in Satellite Imagery
Nathan Mitchell, Lander Ver Hoef, Imme Ebert-Uphoff +4
Machine learning (ML) algorithms have emerged in many meteorological applications. However, these algorithms struggle to extrapolate beyond the data they were trained on, i.e., the…
A Land of Oblique Duality for Frames and Probabilistic Frames
Dongwei Chen, Emily J. King, Clayton Shonkwiler
Functions or distributions used to sample and to reconstruct signals often occur in different domains, like the Dirac delta and a band-limited bump function in classical sampling.…
-Homogeneous Equiangular Tight Frames
Emily J. King
We consider geometric and combinatorial characterizations of equiangular tight frames (ETFs), with the former concerning homogeneity of the vector and line symmetry groups and the…
The impossibility of extending the Naimark complement
Emily J. King, Dustin G. Mixon
We show that there is no extension of the Naimark complement to arbitrary frames that satisfies three fundamental properties of the Naimark complement of Parseval frames.
Approximately Dual and Pseudo-Dual Probabilistic Frames
Dongwei Chen, Emily J. King, Clayton Shonkwiler
This paper studies properties of dual probabilistic frames -- in particular in relation to redundancy -- and introduces both approximately dual probabilistic frames and pseudo-dual…
Connections Between Frames with Rational Eigensteps and Semistandard Young Tableaux
Emily J. King, Kylie Schnoor
In this paper, we explore a correspondence between frames with rational eigensteps and semistandard Young tableaux (SSYT), via the relation assigning a Gelfand-Tsetlin pattern to a…