Skip to main navigation
Skip to search
Skip to main content
Experts@Minnesota Home
Home
Profiles
Research units
University Assets
Projects and Grants
Research output
Datasets
Press/Media
Activities
Fellowships, Honors, and Prizes
Impacts
Search by expertise, name or affiliation
Monotone Generative Modeling via a Gromov-Monge Embedding
Wonjun Lee
, Yifei Yang
, Dongmian Zou
,
Gilad Lerman
School of Mathematics
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Monotone Generative Modeling via a Gromov-Monge Embedding'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Monotone
100%
Encoder
100%
Mode Collapse
100%
Monge
100%
Generative Modeling
100%
Numerical Experiments
50%
High Quality Images
50%
Data Distribution
50%
Low-dimensional Structures
50%
Distribution Map
50%
Modulus of Continuity
50%
Latent Space
50%
Architecture Selection
50%
Generative Adversarial Networks
50%
Cyclic Monotonicity
50%
Popular
50%
Collapse Instability
50%
Reference Measure
50%
Empirical Tuning
50%
Embedded Cost
50%
Training Instability
50%
Embedded Distribution
50%
Mathematics
Key Property
100%
Data Distribution
100%
Numerical Experiment
100%
Dimensional Structure
100%
Computer Science
Underlying Data
100%
Discriminator
50%
Image Quality
50%
Generative Adversarial Networks
50%
Data Distribution
50%
Dimensional Structure
50%