Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Desantis, Derek"'
We present a theory of causality in dynamical systems using Koopman operators. Our theory is grounded on a rigorous definition of causal mechanism in dynamical systems given in terms of flow maps. In the Koopman framework, we prove that causal mechan
Externí odkaz:
http://arxiv.org/abs/2410.10103
Autor:
Danis, Mustafa Engin, Truong, Duc P., DeSantis, Derek, Petersen, Mark, Rasmussen, Kim O., Alexandrov, Boian S.
In this paper, we introduce a high-order tensor-train (TT) finite volume method for the Shallow Water Equations (SWEs). We present the implementation of the $3^{rd}$ order Upwind and the $5^{th}$ order Upwind and WENO reconstruction schemes in the TT
Externí odkaz:
http://arxiv.org/abs/2408.03483
Several Earth system components are at a high risk of undergoing rapid and irreversible qualitative changes or `tipping', due to increasing climate warming. Potential tipping elements include Arctic sea-ice, Atlantic meridional overturning circulatio
Externí odkaz:
http://arxiv.org/abs/2407.17357
Autor:
Xu, Wei, DeSantis, Derek Freeman, Luo, Xihaier, Parmar, Avish, Tan, Klaus, Nadiga, Balu, Ren, Yihui, Yoo, Shinjae
Learning a continuous and reliable representation of physical fields from sparse sampling is challenging and it affects diverse scientific disciplines. In a recent work, we present a novel model called MMGN (Multiplicative and Modulated Gabor Network
Externí odkaz:
http://arxiv.org/abs/2404.06418
We propose a new method for combining in situ buoy measurements with Earth system models (ESMs) to improve the accuracy of temperature predictions in the ocean. The technique utilizes the dynamics \textit{and} modes identified in ESMs alongside buoy
Externí odkaz:
http://arxiv.org/abs/2301.05551
A novel approach to Boolean matrix factorization (BMF) is presented. Instead of solving the BMF problem directly, this approach solves a nonnegative optimization problem with the constraint over an auxiliary matrix whose Boolean structure is identica
Externí odkaz:
http://arxiv.org/abs/2106.04708
The application of binary matrices are numerous. Representing a matrix as a mixture of a small collection of latent vectors via low-rank decomposition is often seen as an advantageous method to interpret and analyze data. In this work, we examine the
Externí odkaz:
http://arxiv.org/abs/2012.10496
A tensor provides a concise way to codify the interdependence of complex data. Treating a tensor as a d-way array, each entry records the interaction between the different indices. Clustering provides a way to parse the complexity of the data into mo
Externí odkaz:
http://arxiv.org/abs/2001.07827
There is an emerging interest in tensor factorization applications in big-data analytics and machine learning. To speed up the factorization of extra-large datasets, organized in multidimensional arrays (aka tensors), easy to compute compression-base
Externí odkaz:
http://arxiv.org/abs/1909.07570
Autor:
DeSantis, Derek
Operator algebras generated by partial isometries and their adjoints form the basis for some of the most well studied classes of C*-algebras. The primary object of this paper is the norm-closed operator algebra generated by a left invertible $T$ toge
Externí odkaz:
http://arxiv.org/abs/1809.04700