Roy R. Lederman

According to our database, Roy R. Lederman authored at least 22 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Efficient high-resolution refinement in cryo-EM with stochastic gradient descent.

Bogdan Toader, Marcus A. Brubaker, Roy R. Lederman

CoRR, 2023

On Manifold Learning in Plato's Cave: Remarks on Manifold Learning and Physical Phenomena.

Roy R. Lederman, Bogdan Toader

CoRR, 2023

Using VAEs to Learn Latent Variables: Observations on Applications in cryo-EM.

Daniel G. Edelberg, Roy R. Lederman

CoRR, 2023

2022

Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals.

James A. Brofos, Marylou Gabrié, Marcus A. Brubaker, Roy R. Lederman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Maximum likelihood for high-noise group orbit estimation and single-particle cryo-EM.

Zhou Fan, Roy R. Lederman, Yi Sun, Tianhao Wang, Sheng Xu

CoRR, 2021

Manifold Density Estimation via Generalized Dequantization.

James A. Brofos, Marcus A. Brubaker, Roy R. Lederman

CoRR, 2021

Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte Carlo.

James A. Brofos, Roy R. Lederman

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Magnetic Manifold Hamiltonian Monte Carlo.

James A. Brofos, Roy R. Lederman

CoRR, 2020

Spectral Flow on the Manifold of SPD Matrices for Multimodal Data Processing.

Ori Katz, Roy R. Lederman, Ronen Talmon

CoRR, 2020

Non-Canonical Hamiltonian Monte Carlo.

James A. Brofos, Roy R. Lederman

CoRR, 2020

2019

Extreme Values of the Fiedler Vector on Trees.

Roy R. Lederman, Stefan Steinerberger

CoRR, 2019

Hyper-Molecules: on the Representation and Recovery of Dynamical Structures, with Application to Flexible Macro-Molecular Structures in Cryo-EM.

Roy R. Lederman, Joakim Andén, Amit Singer

CoRR, 2019

2018

Learning by coincidence: Siamese networks and common variable learning.

Uri Shaham, Roy R. Lederman

Pattern Recognit., 2018

Heterogeneous multireference alignment: A single pass approach.

Nicolas Boumal, Tamir Bendory, Roy R. Lederman, Amit Singer

Proceedings of the 52nd Annual Conference on Information Sciences and Systems, 2018

2017

Numerical Algorithms for the Computation of Generalized Prolate Spheroidal Functions.

Roy R. Lederman

CoRR, 2017

Continuously heterogeneous hyper-objects in cryo-EM and 3-D movies of many temporal dimensions.

Roy R. Lederman, Amit Singer

CoRR, 2017

2016

On the Analytical and Numerical Properties of the Truncated Laplace Transform. Part II.

Roy R. Lederman, Vladimir Rokhlin

SIAM J. Numer. Anal., 2016

A Representation Theory Perspective on Simultaneous Alignment and Classification.

Roy R. Lederman, Amit Singer

CoRR, 2016

2015

On the Analytical and Numerical Properties of the Truncated Laplace Transform I.

Roy R. Lederman, Vladimir Rokhlin

SIAM J. Numer. Anal., 2015

Common Variable Learning and Invariant Representation Learning using Siamese Neural Networks.

Uri Shaham, Roy R. Lederman

CoRR, 2015

Alternating diffusion for common manifold learning with application to sleep stage assessment.

Roy R. Lederman, Ronen Talmon, Hau-Tieng Wu, Yu-Lun Lo, Ronald R. Coifman

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2013

A random-permutations-based approach to fast read alignment.

Roy R. Lederman

BMC Bioinform., 2013