nGraph-HE: A Graph Compiler for Deep Learning on Homomorphically Encrypted Data. - Fabian Boemer; Yixing Lao; Casimir Wierzynski (CoRR, 2018)

Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics. - Yaron Meirovitch; Lu Mi; Hayk Saribekyan; Alexander Matveev; David Rolnick; Casimir Wierzynski; Nir Shavit (CoRR, 2018)

nGraph-HE2: A High-Throughput Framework for Neural Network Inference on Encrypted Data. - Fabian Boemer; Anamaria Costache; Rosario Cammarota; Casimir Wierzynski (WAHC@CCS, 2019)

nGraph-HE: a graph compiler for deep learning on homomorphically encrypted data. - Fabian Boemer; Yixing Lao; Rosario Cammarota; Casimir Wierzynski (CF, 2019)

Optimizing User Interface Layouts via Gradient Descent. - Peitong Duan; Casimir Wierzynski; Lama Nachman (CHI, 2020)

Design of optical neural networks with component imprecisions. - Michael Y.-S. Fang; Sasikanth Manipatruni; Casimir Wierzynski; Amir Khosrowshahi; Michael Robert DeWeese (CoRR, 2020)

Learning Irreducible Representations of Noncommutative Lie Groups. - Noah Shutty; Casimir Wierzynski (CoRR, 2020)

Computing representations for Lie algebraic networks. - Noah Shutty; Casimir Wierzynski (NeurReps, 2022)