• M. Mousavi, E. Lybrand, S. Feng, S. Tang, R. Saab, and V. de Sa. “Spectrally Adaptive Common Spatial Patterns”. Preprint. arXiv

  • E. Lybrand and R. Saab. “A Greedy Algorithm for Quantizing Neural Networks.” JMLR 2021. arXiv Journal GitHub

  • E. Lybrand, A. Ma, and R. Saab. “On the Number of Faces and Radii of Cells Induced by Gaussian Spherical Tessellations.” ACHA, 2021. arXiv Journal

  • 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