An aberrant increase in pluripotency gene (PpG) expression due to enhancer reactivation
could induce stemness and enhance the tumorigenicity of cancer stem cells. Silencing of PpG …

Background Carcinoma–associated fibroblasts (CAF) are a heterogeneous group of cells
within the tumor microenvironment (TME) that can promote tumorigenesis in the prostate. By …

In this paper we describe a method for computing item based recommendations using matrix-factorization-like
embeddings of the items computed using a neural network. Matrix …

This paper addresses challenges in flexibly modeling multimodal data that lie on constrained
spaces. Such data are commonly found in spatial applications, such as climatology and …

Embedding based product recommendations have gained popularity in recent years due to
its ability to easily integrate to large-scale systems and allowing nearest neighbor searches …

This paper addresses challenges in flexibly modeling multimodal data that lie on constrained
spaces. Such data are commonly found in spatial applications, such as climatology and …

Mixture modeling is a classical unsupervised learning method with applications to clustering
and density estimation. This dissertation studies two challenges in modeling data with …

Markov jump processes are continuous-time stochastic processes widely used in a variety
of applied disciplines. Inference typically proceeds via Markov chain Monte Carlo (MCMC), …

Antimicrobial resistance (AMR) is a major challenge to modern medicine and of grave concern
to public health. To monitor AMR, researchers analyze “drug/bug” collections of clinical …

Networks and point processes provide flexible tools for representing and modeling complex
dependencies in data arising from various social and physical domains. Graphs, or networks…