research
∙
06/30/2023
Quantum State Assignment Flows
This paper introduces assignment flows for density matrices as state spa...
share
research
∙
06/23/2023
On the Convergence Rate of Gaussianization with Random Rotations
Gaussianization is a simple generative model that can be trained without...
research
∙
06/15/2023
On Certified Generalization in Structured Prediction
In structured prediction, target objects have rich internal structure wh...
research
∙
10/25/2022
Whitening Convergence Rate of Coupling-based Normalizing Flows
Coupling-based normalizing flows (e.g. RealNVP) are a popular family of ...
research
∙
05/09/2022
A Nonlocal Graph-PDE and Higher-Order Geometric Integration for Image Labeling
This paper introduces a novel nonlocal partial difference equation (PDE)...
research
∙
01/26/2022
Self-Certifying Classification by Linearized Deep Assignment
We propose a novel class of deep stochastic predictors for classifying m...
research
∙
01/21/2022
Multi-view Monocular Depth and Uncertainty Prediction with Deep SfM in Dynamic Environments
3D reconstruction of depth and motion from monocular video in dynamic en...
research
∙
08/19/2021
Learning System Parameters from Turing Patterns
The Turing mechanism describes the emergence of spatial patterns due to ...
research
∙
08/02/2021
Learning Linearized Assignment Flows for Image Labeling
We introduce a novel algorithm for estimating optimal parameters of line...
research
∙
02/26/2020
Assignment Flows for Data Labeling on Graphs: Convergence and Stability
The assignment flow recently introduced in the J. Math. Imaging and Visi...
research
∙
11/13/2019
Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least-Squares Case
In this paper we conduct a study of both superiorization and optimizatio...
research
∙
11/08/2019
Self-Assignment Flows for Unsupervised Data Labeling on Graphs
This paper extends the recently introduced assignment flow approach for ...
research
∙
10/22/2019
Learning Adaptive Regularization for Image Labeling Using Geometric Assignment
We study the inverse problem of model parameter learning for pixelwise i...
research
∙
10/16/2019
Continuous-Domain Assignment Flows
Assignment flows denote a class of dynamical models for contextual data ...
research
∙
06/11/2019
Approximate Variational Inference Based on a Finite Sample of Gaussian Latent Variables
Variational methods are employed in situations where exact Bayesian infe...
research
∙
04/24/2019
Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment
This paper introduces the unsupervised assignment flow that couples the ...
research
∙
05/18/2018
Fast Multivariate Log-Concave Density Estimation
We present a computational approach to log-concave density estimation. T...
research
∙
10/04/2017
Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment
We introduce a novel approach to Maximum A Posteriori inference based on...
research
∙
08/21/2017
Sum-Product Graphical Models
This paper introduces a new probabilistic architecture called Sum-Produc...
research
∙
07/25/2016
Symmetry-free SDP Relaxations for Affine Subspace Clustering
We consider clustering problems where the goal is to determine an optima...
research
∙
06/07/2016
Joint Recursive Monocular Filtering of Camera Motion and Disparity Map
Monocular scene reconstruction is essential for modern applications such...
research
∙
05/19/2016
A Geometric Approach to Color Image Regularization
We present a new vectorial total variation method that addresses the pro...
research
∙
03/16/2016
Image Labeling by Assignment
We introduce a novel geometric approach to the image labeling problem. A...
research
∙
01/09/2016
Multicuts and Perturb & MAP for Probabilistic Graph Clustering
We present a probabilistic graphical model formulation for the graph clu...
research
∙
10/24/2014
Partial Optimality by Pruning for MAP-Inference with General Graphical Models
We consider the energy minimization problem for undirected graphical mod...
research
∙
07/15/2014
Globally Optimal Joint Image Segmentation and Shape Matching Based on Wasserstein Modes
A functional for joint variational object segmentation and shape matchin...
research
∙
07/03/2014
Solving QVIs for Image Restoration with Adaptive Constraint Sets
We consider a class of quasi-variational inequalities (QVIs) for adaptiv...
research
∙
11/28/2013
Shape from Texture using Locally Scaled Point Processes
Shape from texture refers to the extraction of 3D information from 2D im...
research
∙
09/09/2013
Contour Manifolds and Optimal Transport
Describing shapes by suitable measures in object segmentation, as propos...
research
∙
01/16/2013
Convex Variational Image Restoration with Histogram Priors
We present a novel variational approach to image restoration (e.g., deno...
research
∙
12/05/2011
Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem
We consider a variational convex relaxation of a class of optimal partit...
research
∙
02/26/2011
