Michael Lindsey

According to our database, Michael Lindsey authored at least 21 papers between 2017 and 2025.

Collaborative distances:

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

2025

MNE: overparametrized neural evolution with applications to diffusion processes and sampling.

Michael Lindsey

CoRR, February, 2025

2024

Multiscale Semidefinite Programming Approach to Positioning Problems with Pairwise Structure.

Yian Chen, Yuehaw Khoo, Michael Lindsey

J. Sci. Comput., November, 2024

Scalable semidefinite programming approach to variational embedding for quantum many-body problems.

Yuehaw Khoo, Michael Lindsey

J. Comput. Phys., 2024

A gradient-based and determinant-free framework for fully Bayesian Gaussian process regression.

P. Michael Kielstra, Michael Lindsey

CoRR, 2024

Gaussian process regression with log-linear scaling for common non-stationary kernels.

P. Michael Kielstra, Michael Lindsey

CoRR, 2024

Column and row subset selection using nuclear scores: algorithms and theory for Nyström approximation, CUR decomposition, and graph Laplacian reduction.

Mark Fornace, Michael Lindsey

CoRR, 2024

Direct interpolative construction of the discrete Fourier transform as a matrix product operator.

Jielun Chen, Michael Lindsey

CoRR, 2024

Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization.

Yuhang Cai, Jingfeng Wu, Song Mei, Michael Lindsey, Peter L. Bartlett

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Multimarginal Generative Modeling with Stochastic Interpolants.

Michael S. Albergo, Nicholas Matthew Boffi, Michael Lindsey, Eric Vanden-Eijnden

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Committor functions via tensor networks.

Yian Chen, Jeremy G. Hoskins, Yuehaw Khoo, Michael Lindsey

J. Comput. Phys., 2023

Multiscale interpolative construction of quantized tensor trains.

Michael Lindsey

CoRR, 2023

Tensorizing flows: a tool for variational inference.

Yuehaw Khoo, Michael Lindsey, Hongli Zhao

CoRR, 2023

Fast randomized entropically regularized semidefinite programming.

Michael Lindsey

CoRR, 2023

2022

Ensemble Markov Chain Monte Carlo with Teleporting Walkers.

Michael Lindsey, Jonathan Weare, Anna Zhang

SIAM/ASA J. Uncertain. Quantification, 2022

Towards sharp error analysis of extended Lagrangian molecular dynamics.

Dong An, Lin Lin, Michael Lindsey

J. Comput. Phys., 2022

Understanding and eliminating spurious modes in variational Monte Carlo using collective variables.

Huan Zhang, Robert J. Webber, Michael Lindsey, Timothy C. Berkelbach, Jonathan Weare

CoRR, 2022

Generative modeling via tensor train sketching.

Yoonhaeng Hur, Jeremy G. Hoskins, Michael Lindsey, E. Miles Stoudenmire, Yuehaw Khoo

CoRR, 2022

2021

Rayleigh-Gauss-Newton optimization with enhanced sampling for variational Monte Carlo.

Robert J. Webber, Michael Lindsey

CoRR, 2021

2020

Semidefinite Relaxation of Multimarginal Optimal Transport for Strictly Correlated Electrons in Second Quantization.

Yuehaw Khoo, Lin Lin, Michael Lindsey, Lexing Ying

SIAM J. Sci. Comput., 2020

2019

Variational embedding for quantum many-body problems.

Lin Lin, Michael Lindsey

CoRR, 2019

2017

Optimal Transport via a Monge-Ampère Optimization Problem.

Michael Lindsey, Yanir A. Rubinstein

SIAM J. Math. Anal., 2017