Image Generation On Mnist
Metrics
FID
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | FID |
|---|---|
| Model 1 | 7.95 |
| spiking-diffusion-vector-quantized-discrete | 27.61 |
| locally-masked-convolution-for-autoregressive | - |
| generative-latent-flow-a-framework-for-non | 5.8 |
| explainable-deep-learning-a-visual-analytics | - |
| hyperbolic-generative-adversarial-network | 7.87 |
| prescribed-generative-adversarial-networks | 38.53 |
| feature-alignment-for-approximated | 37.50 |
| sliced-iterative-generator | 4.5 |
| Model 10 | 12.884 |
| how-to-train-your-neural-ode | - |
| residual-flows-for-invertible-generative | - |
| mintnet-building-invertible-neural-networks | - |
| Model 14 | 4.45 |
| invertible-residual-networks | - |