MNIST Fashion

The MNIST Fashion dataset contains images of clothing items and is used to evaluate the performance of generative models, particularly in the context of handling imbalanced datasets.

Papers using MNIST Fashion (18)

Multivariate Variational Autoencoder2025Toward Architecture-Agnostic Local Control of Posterior Collapse in VAEs2025Bidirectional Variational Autoencoders2025Deep Generative Clustering with VAEs and Expectation-Maximization2025Generalization Bound for Diffusion Models using Random Features2023Multilinear Latent Conditioning for Generating Unseen Attribute Combinations2020 · 7 citesWasserstein-Wasserstein Auto-Encoders2019 · 5 citesFIS-GAN: GAN with Flow-based Importance Sampling2019 · 2 citesOptimal Transport Based Generative Autoencoders2019 · 1 citesTeaching a GAN What Not to Learn2020 · 1 citesConditional Variational Autoencoder with Balanced Pre-training for Generative Adversarial Networks2022 · 1 citesSDiT: Spiking Diffusion Model with Transformer2024 · 1 citesA Gauss-Newton Approach for Min-Max Optimization in Generative Adversarial Networks2024 · 1 citesPixel-wise Conditioning of Generative Adversarial Networks2019Generative Models from the perspective of Continual Learning2018Training generative networks using random discriminators2019Hierarchical Mixtures of Generators for Adversarial Learning2019Enhanced Balancing GAN: Minority-class Image Generation2020