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Biorxiv : the Preprint Server for Biology|July 29, 2026
Best for the Eye, Not for the Algorithm: Anisotropy in Fitting Atomic Models in Cryo-EMRoey Yadgar, Roy R Lederman... International Conference on Sampling Theory and Applications (Sampta). International Conference on Sampling Theory and Applications|March 4, 2024
On Manifold Learning in Plato's Cave: Remarks on Manifold Learning and Physical PhenomenaRoy R Lederman, Bogdan ToaderApplied and Computational Harmonic Analysis|August 15, 2024
A Representation Theory Perspective on Simultaneous Alignment and ClassificationRoy R Lederman, Amit SingerLinear Algebra and Its Applications|December 9, 2024
EXTREME VALUES OF THE FIEDLER VECTOR ON TREESRoy R Lederman, Stefan SteinerbergerProceedings of Machine Learning Research|August 19, 2022
Evaluating the Implicit Midpoint Integrator for Riemannian Manifold Hamiltonian Monte CarloJames A Brofos, Roy R LedermanArxiv|March 30, 2023
Using VAEs to Learn Latent Variables: Observations on Applications in cryo-EMDaniel G Edelberg, Roy R LedermanInverse Problems|February 2, 2024
Hyper-Molecules: on the Representation and Recovery of Dynamical Structures for Applications in Flexible Macro-Molecules in Cryo-EMRoy R Lederman, Joakim Andén, Amit SingerJournal of Molecular Biology|March 2, 2023
Methods for Cryo-EM Single Particle Reconstruction of Macromolecules Having Continuous HeterogeneityBogdan Toader, Fred J Sigworth, Roy R LedermanActa Crystallographica. Section D, Structural Biology|June 23, 2025
Efficient high-resolution refinement in cryo-EM with stochastic gradient descentBogdan Toader, Marcus A Brubaker, Roy R LedermanArxiv|December 11, 2023
Efficient high-resolution refinement in cryo-EM with stochastic gradient descentBogdan Toader, Marcus A Brubaker, Roy R LedermanPageof 2