RESEARCH PAPERYear 2017

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

Martin Heusel; Hubert Ramsauer; Thomas Unterthiner; Bernhard Nessler; Sepp Hochreiter

Read paper PDF

Classification

View four quadrants

Major category: Evaluation metrics
Quadrant: Not applicable
Architecture: Not applicable
Prediction paradigm: Not applicable
Subcategories: Image quality metrics Evaluation metrics & protocols Training optimization & distillation
Source review status: Explicit in survey

AT A GLANCE

Contribution

A contribution summary has not been added yet.

Abstract

An abstract has not been added yet.

Affiliations

Not listed in the collection.

BibTeX

@inproceedings{fid,
  title={{GANs} Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium},
  author={Heusel, Martin and Ramsauer, Hubert and Unterthiner, Thomas and Nessler, Bernhard and Hochreiter, Sepp},
  booktitle={NeurIPS},
  year={2017}
}

Classification

Contribution

Abstract

Affiliations

BibTeX

More in this category

Beyond Task Success: Stage-Wise Reliability of World Model Planning under Sensing Degradation

Paired Exact-Reset Evaluation of a Prediction-Derived Medium-to-Full World-Model Cascade

Beyond Task Success: Behavioral and Representational Diagnostics for WAM and VLA