6 papers
GoForth: Language Models for RNA Design under Structure, Sequence, and Coding Constraints
Michael Lindsey
RNA inverse sequence design has broad biological and engineering applications, but computational methods for practical design queries remain limited. Such queries may impose severa…
An approximation theory for Markov chain compression
Mark Fornace, Michael Lindsey
We develop a framework for the compression of reversible Markov chains with rigorous error control. Given a subset of selected states, we construct reduced dynamics that can be lif…
Fast entropy-regularized SDP relaxations for permutation synchronization
Michael Lindsey, Yunpeng Shi
We introduce fast randomized algorithms for solving semidefinite programming (SDP) relaxations of the partial permutation synchronization (PPS) problem, a core task in multi-image…
Improved energies and wave function accuracy with Weighted Variational Monte Carlo
Huan Zhang, Robert J. Webber, Michael Lindsey +2
Neural network parametrizations have increasingly been used to represent the ground and excited states in variational Monte Carlo (VMC) with promising results. However, traditional…
Simple Diagonal State Designs with Reconfigurable Real-Time Circuits
Yizhi Shen, Katherine Klymko, Eran Rabani +4
Unitary designs are widely used in quantum computation, but in many practical settings it suffices to construct a diagonal state design generated with unitary gates diagonal in the…
MNE: overparametrized neural evolution with applications to diffusion processes and sampling
Michael Lindsey
We propose a framework for solving evolution equations within parametric function classes, especially ones that are specified by neural networks. We call this framework the minimal…