Convolution Acceleration: Query Based Filter Pruning. - Arthur Feeney; Yu Zhang 150 (SMC, 2019)

Relation Matters in Sampling: A Scalable Multi-Relational Graph Neural Network for Drug-Drug Interaction Prediction. - Arthur Feeney; Rishabh Gupta; Veronika Thost; Rico Angell; Gayathri Chandu; Yash Adhikari; Tengfei Ma 001 (CoRR, 2021)

BubbleML: A Multiphase Multiphysics Dataset and Benchmarks for Machine Learning. - Sheikh Md Shakeel Hassan; Arthur Feeney; Akash Dhruv; Jihoon Kim; Youngjoon Suh; Jaiyoung Ryu; Yoonjin Won; Aparna Chandramowlishwaran (NeurIPS, 2023)

Breaking Boundaries: Distributed Domain Decomposition with Scalable Physics-Informed Neural PDE Solvers. - Arthur Feeney; Zitong Li; Ramin Bostanabad; Aparna Chandramowlishwaran (SC, 2023)

BubbleML: A Multi-Physics Dataset and Benchmarks for Machine Learning. - Sheikh Md Shakeel Hassan; Arthur Feeney; Akash Dhruv; Jihoon Kim; Youngjoon Suh; Jaiyoung Ryu; Yoonjin Won; Aparna Chandramowlishwaran (CoRR, 2023)

BERN-NN-IBF: Enhancing Neural Network Bound Propagation Through Implicit Bernstein Form and Optimized Tensor Operations. - Wael Fatnassi; Arthur Feeney; Valen Yamamoto; Aparna Chandramowlishwaran; Yasser Shoukry (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

Mondrian: Transformer Operators via Domain Decomposition. - Arthur Feeney; Kuei-Hsiang Huang; Aparna Chandramowlishwaran (CoRR, 2025)