3 citations · 4 across the 6 of their papers we have counts for
6 papers
In-depth Analysis On Parallel Processing Patterns for High-Performance Dataframes
Niranda Perera, Arup Kumar Sarker, Mills Staylor +7
The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intel…
Hybrid Reusable Computational Analytics Workflow Management with Cloudmesh
Gregor von Laszewski, J. P. Fleischer, Geoffrey C. Fox
In this paper, we summarize our effort to create and utilize a simple framework to coordinate computational analytics tasks with the help of a workflow system. Our design is based…
Time Series Analysis of Blockchain-Based Cryptocurrency Price Changes
Jacques Fleischer, Gregor von Laszewski, Carlos Theran +1
In this paper we apply neural networks and Artificial Intelligence (AI) to historical records of high-risk cryptocurrency coins to train a prediction model that guesses their price…
HPTMT Parallel Operators for High Performance Data Science & Data Engineering
Vibhatha Abeykoon, Supun Kamburugamuve, Chathura Widanage +5
Data-intensive applications are becoming commonplace in all science disciplines. They are comprised of a rich set of sub-domains such as data engineering, deep learning, and machin…
HPTMT: Operator-Based Architecture for Scalable High-Performance Data-Intensive Frameworks
Supun Kamburugamuve, Chathura Widanage, Niranda Perera +5
Data-intensive applications impact many domains, and their steadily increasing size and complexity demands high-performance, highly usable environments. We integrate a set of ideas…
AICov: An Integrative Deep Learning Framework for COVID-19 Forecasting with Population Covariates
Geoffrey C. Fox, Gregor von Laszewski, Fugang Wang +1
The COVID-19 pandemic has profound global consequences on health, economic, social, political, and almost every major aspect of human life. Therefore, it is of great importance to…