research
∙
06/05/2023
Convex Relaxation for Fokker-Planck
We propose an approach to directly estimate the moments or marginals for...
share
research
∙
05/29/2023
Combining Particle and Tensor-network Methods for Partial Differential Equations via Sketching
In this paper, we propose a general framework for solving high-dimension...
research
∙
05/03/2023
Tensorizing flows: a tool for variational inference
Fueled by the expressive power of deep neural networks, normalizing flow...
research
∙
04/28/2023
Deep Neural-network Prior for Orbit Recovery from Method of Moments
Orbit recovery problems are a class of problems that often arise in prac...
research
∙
04/11/2023
Generative Modeling via Hierarchical Tensor Sketching
We propose a hierarchical tensor-network approach for approximating high...
research
∙
12/01/2022
High-dimensional density estimation with tensorizing flow
We propose the tensorizing flow method for estimating high-dimensional p...
research
∙
09/21/2022
Autocorrelation analysis for cryo-EM with sparsity constraints: Improved sample complexity and projection-based algorithms
The number of noisy images required for molecular reconstruction in sing...
research
∙
09/03/2022
Generative Modeling via Tree Tensor Network States
In this paper, we present a density estimation framework based on tree t...
research
∙
06/08/2022
Reinforced Inverse Scattering
Inverse wave scattering aims at determining the properties of an object ...
research
∙
12/25/2021
A Spectral Method for Joint Community Detection and Orthogonal Group Synchronization
Community detection and orthogonal group synchronization are both fundam...
research
∙
06/23/2021
Committor functions via tensor networks
We propose a novel approach for computing committor functions, which des...
research
∙
05/13/2021
Joint Community Detection and Rotational Synchronization via Semidefinite Programming
In the presence of heterogeneous data, where randomly rotated objects fa...
research
∙
12/18/2020
Multiscale semidefinite programming approach to positioning problems with pairwise structure
We consider the optimization of pairwise objective functions, i.e., obje...
research
∙
12/12/2020
Solving for high dimensional committor functions using neural network with online approximation to derivatives
This paper proposes a new method based on neural networks for computing ...
research
∙
08/09/2020
NMR Assignment through Linear Programming
Nuclear Magnetic Resonance (NMR) Spectroscopy is the second most used te...
research
∙
07/11/2019
Method of moments for 3-D single particle ab initio modeling with non-uniform distribution of viewing angles
Single-particle reconstruction in cryo-electron microscopy (cryo-EM) is ...
research
∙
10/23/2018
SwitchNet: a neural network model for forward and inverse scattering problems
We propose a novel neural network architecture, SwitchNet, for solving t...
research
∙
02/28/2018
Solving for high dimensional committor functions using artificial neural networks
In this note we propose a method based on artificial neural network to s...
research
∙
01/04/2015
Non-iterative rigid 2D/3D point-set registration using semidefinite programming
We describe a convex programming framework for pose estimation in 2D/3D ...
research
∙
04/10/2014
Open problem: Tightness of maximum likelihood semidefinite relaxations
We have observed an interesting, yet unexplained, phenomenon: Semidefini...
research
∙
06/21/2013
