Abstract Machine learning, and especially deep learning, is rapidly gaining acceptance and
clinical usage in a wide range of image analysis applications and is regarded as providing …

We study linear filters for processing signals supported on abstract topological spaces
modeled as simplicial complexes, which may be interpreted as generalizations of graphs …

We present Topological Point Cloud Clustering (TPCC), a new method to cluster points in an
arbitrary point cloud based on their contribution to global topological features. TPCC …

Identifying (a) systemic barriers to quality healthcare access and (b) key indicators of care
efficacy in the United States remains a significant challenge. To improve our understanding …

To address the peculiarities of directed and/or signed graphs, new Laplacian operators have
emerged. For instance, in the case of directionality, we encounter the magnetic operator …

Simplicial convolutional filters can process signals defined over levels of a simplicial
complex such as nodes, edges, triangles, and so on with applications in eg, flow prediction …

Nesta tese, exploramos a interseção entre grafos, grupos e termodinâmica, empregando
uma variedade de ferramentas analíticas e computacionais recentes. O estudo se concentra …

Graph-based machine learning has seen significant growth during the past years with great
advancements and applicability. These approaches mostly focus on pairwise interactions …

Network analysis has been identified as an important approach for understanding and
improving large scale health system operations. This review sought to understand the …

Advocates of healthcare reform are hopeful that accountable care organizations (ACOs) will
not only help to bend the healthcare spending curve, but also lead to better quality, through …