Michael Lindsey

36 papers A* 3Journal 33

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Gradient-based and Determinant-free Framework for Fully Bayesian Gaussian Process Regression. SIAM/ASA J. Uncertain. Quantification P. Michael Kielstra, Michael Lindsey
2025	J	`jnl`	An approximation theory for Markov chain compression. CoRR Mark Fornace, Michael Lindsey
2025	J	`jnl`	Fast and Accurate Interpolative Decompositions for General, Sparse, and Structured Tensors. CoRR Yifan Zhang, Mark Fornace, Michael Lindsey
2025	J	`jnl`	Fast entropy-regularized SDP relaxations for permutation synchronization. CoRR Michael Lindsey, Yunpeng Shi
2025	J	`jnl`	Geometric adaptive smoothed aggregation multigrid for discontinuous Galerkin discretisations. CoRR Yulong Pan, Michael Lindsey, Per-Olof Persson
2025	A*	`conf`	Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks. ICML Yuhang Cai, Kangjie Zhou, Jingfeng Wu, Song Mei, Michael Lindsey, Peter L. Bartlett
2025	J	`jnl`	Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks. CoRR Yuhang Cai, Kangjie Zhou, Jingfeng Wu, Song Mei, Michael Lindsey, Peter L. Bartlett
2025	J	`jnl`	MNE: overparametrized neural evolution with applications to diffusion processes and sampling. CoRR Michael Lindsey
2025	J	`jnl`	Non-Euclidean dual gradient ascent for entropically regularized linear and semidefinite programming. CoRR Yuhang Cai, Michael Lindsey
2025	J	`jnl`	Toward optimal-scaling DFT: stochastic Hartree theory in the thermodynamic and complete basis set limits at arbitrary temperature. CoRR Yuhang Cai, Michael Lindsey
2024	J	`jnl`	A gradient-based and determinant-free framework for fully Bayesian Gaussian process regression. CoRR P. Michael Kielstra, Michael Lindsey
2024	J	`jnl`	Column and row subset selection using nuclear scores: algorithms and theory for Nyström approximation, CUR decomposition, and graph Laplacian reduction. CoRR Mark Fornace, Michael Lindsey
2024	J	`jnl`	Direct interpolative construction of the discrete Fourier transform as a matrix product operator. CoRR Jielun Chen, Michael Lindsey
2024	J	`jnl`	Gaussian process regression with log-linear scaling for common non-stationary kernels. CoRR P. Michael Kielstra, Michael Lindsey
2024	A*	`conf`	Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization. NeurIPS Yuhang Cai, Jingfeng Wu, Song Mei, Michael Lindsey, Peter L. Bartlett
2024	J	`jnl`	Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization. CoRR Yuhang Cai, Jingfeng Wu, Song Mei, Michael Lindsey, Peter L. Bartlett
2024	A*	`conf`	Multimarginal Generative Modeling with Stochastic Interpolants. ICLR Michael S. Albergo, Nicholas Matthew Boffi, Michael Lindsey, Eric Vanden-Eijnden
2024	J	`jnl`	Multiscale Semidefinite Programming Approach to Positioning Problems with Pairwise Structure. J. Sci. Comput. Yian Chen, Yuehaw Khoo, Michael Lindsey
2024	J	`jnl`	Scalable semidefinite programming approach to variational embedding for quantum many-body problems. J. Comput. Phys. Yuehaw Khoo, Michael Lindsey
2023	J	`jnl`	Committor functions via tensor networks. J. Comput. Phys. Yian Chen, Jeremy G. Hoskins, Yuehaw Khoo, Michael Lindsey
2023	J	`jnl`	Fast randomized entropically regularized semidefinite programming. CoRR Michael Lindsey
2023	J	`jnl`	Multimarginal generative modeling with stochastic interpolants. CoRR Michael S. Albergo, Nicholas M. Boffi, Michael Lindsey, Eric Vanden-Eijnden
2023	J	`jnl`	Multiscale interpolative construction of quantized tensor trains. CoRR Michael Lindsey
2023	J	`jnl`	Tensorizing flows: a tool for variational inference. CoRR Yuehaw Khoo, Michael Lindsey, Hongli Zhao
2022	J	`jnl`	Ensemble Markov Chain Monte Carlo with Teleporting Walkers. SIAM/ASA J. Uncertain. Quantification Michael Lindsey, Jonathan Weare, Anna Zhang
2022	J	`jnl`	Generative modeling via tensor train sketching. CoRR Yoonhaeng Hur, Jeremy G. Hoskins, Michael Lindsey, E. Miles Stoudenmire, Yuehaw Khoo
2022	J	`jnl`	Towards sharp error analysis of extended Lagrangian molecular dynamics. J. Comput. Phys. Dong An, Lin Lin, Michael Lindsey
2022	J	`jnl`	Understanding and eliminating spurious modes in variational Monte Carlo using collective variables. CoRR Huan Zhang, Robert J. Webber, Michael Lindsey, Timothy C. Berkelbach, Jonathan Weare
2021	J	`jnl`	Committor functions via tensor networks. CoRR Yian Chen, Jeremy G. Hoskins, Yuehaw Khoo, Michael Lindsey
2021	J	`jnl`	Ensemble Markov chain Monte Carlo with teleporting walkers. CoRR Michael Lindsey, Jonathan Weare, Anna Zhang
2021	J	`jnl`	Rayleigh-Gauss-Newton optimization with enhanced sampling for variational Monte Carlo. CoRR Robert J. Webber, Michael Lindsey
2020	J	`jnl`	Multiscale semidefinite programming approach to positioning problems with pairwise structure. CoRR Yian Chen, Yuehaw Khoo, Michael Lindsey
2020	J	`jnl`	Semidefinite Relaxation of Multimarginal Optimal Transport for Strictly Correlated Electrons in Second Quantization. SIAM J. Sci. Comput. Yuehaw Khoo, Lin Lin, Michael Lindsey, Lexing Ying
2020	J	`jnl`	Towards sharp error analysis of extended Lagrangian molecular dynamics. CoRR Dong An, Lin Lin, Michael Lindsey
2019	J	`jnl`	Variational embedding for quantum many-body problems. CoRR Lin Lin, Michael Lindsey
2017	J	`jnl`	Optimal Transport via a Monge-Ampère Optimization Problem. SIAM J. Math. Anal. Michael Lindsey, Yanir A. Rubinstein