Rapid, Progressive Sub-Graph Explorations for Interactive Visual Analytics over Large-Scale Graph Datasets. - Samuel Armstrong; Kevin Bruhwiler; Sangmi Lee Pallickara (BDCAT, 2019)

Lightweight, Embeddings Based Storage and Model Construction Over Satellite Data Collections. - Kevin Bruhwiler; Paahuni Khandelwal; Daniel Rammer; Samuel Armstrong; Sangmi Lee Pallickara; Shrideep Pallickara (IEEE BigData, 2020)

Small is Beautiful: Distributed Orchestration of Spatial Deep Learning Workloads. - Daniel Rammer; Kevin Bruhwiler; Paahuni Khandelwal; Samuel Armstrong; Shrideep Pallickara; Sangmi Lee Pallickara (UCC, 2020)

CloudNet: A Deep Learning Approach for Mitigating Occlusions in Landsat-8 Imagery using Data Coalescence. - Paahuni Khandelwal; Samuel Armstrong; Abdul Matin; Shrideep Pallickara; Sangmi Lee Pallickara (e-Science, 2022)

Reconsidering an Agent-Based Model of Food Web Evolution. - Samuel Armstrong; Emma Norling (MABS, 2022)

Rapid Betweenness Centrality Estimates for Transportation Networks using Capsule Networks. - Abdul Matin; Samuel Armstrong; Saptashwa Mitra; Shrideep Pallickara; Sangmi Lee Pallickara (TransAI, 2022)

Survey of Machine Learning Techniques To Predict Heartbeat Arrhythmias. - Samuel Armstrong (CoRR, 2022)

Attention-based convolutional capsules for evapotranspiration estimation at scale. - Samuel Armstrong; Paahuni Khandelwal; Dhruv Padalia; Gabriel B. Senay; Darin Schulte; Allan A. Andales; F. Jay Breidt; Shrideep Pallickara; Sangmi Lee Pallickara (Environ. Model. Softw., 2022)

Unconscious Influences on "Free Will" Movement Initiation: Slow-wave Brain Stimulation and the Readiness Potential. - Samuel Armstrong; Nicholas S. Bland; Martin V. Sale; Ross Cunnington (J. Cogn. Neurosci., 2022)