• E. Lybrand and R. Saab. “A Greedy Algorithm for Quantizing Neural Networks.” Accepted by JMLR, in revision 2020. arXiv GitHub

  • E. Lybrand, A. Ma, and R. Saab. “On the Number of Faces and Radii of Cells Induced by Gaussian Spherical Tessellations.” Accepted by ACHA, in revision 2020.

  • H. Huang and T. Kemp and Y. Ling and X. Luo and E. Lybrand and R. Smith and J. Wang. “Random Matrices with Independent Diagonals.” preprint, 2018.


  • M. Iwen, E. Lybrand, A. Nelson, R. Saab. “New Algorithms and Improved Guarantees for One-Bit Compressed Sensing on Manifolds.” SampTA2019. arXiv Proceedings

  • E. Lybrand and R. Saab. “Quantization for Low-Rank Matrix Recovery.” Information and Inference, 2018. arXiv Journal

Selected Talks & Conference Presentations

  • Graduate Student Seminar, UCSD. “Deterministic Models for Topoisomerase II.” February 2017. Slides