MNIST

Dataset Card for MNIST Dataset Summary The MNIST dataset consists of 70,000 28x28 black-and-white images of handwritten digits extracted from two NIST databases. There are 60,000 images in the training dataset and 10,000 images in the validation dataset, one class per digit so a total of 10 classes, with 7,000 images (

Papers using MNIST (94)

Population-Based Multi-Objective Training of Discriminators for Semi-Supervised GANs2026An Hybrid Quantum-Classical Diffusion Model for Image Generation2026Deep Generative Clustering with VAEs and Expectation-Maximization2025 · 1 citesODE-free Neural Flow Matching for One-Step Generative Modeling2026Rethinking Refinement: Correcting Generative Bias without Noise Injection2026Latent Nonlinear Denoising Score Matching for Enhanced Learning of Structured Distributions2025TRISKELION-1: Unified Descriptive-Predictive-Generative AI2025Disentanglement of Sources in a Multi-Stream Variational Autoencoder2025Scaling Non-Parametric Sampling with Representation2025Toward Architecture-Agnostic Local Control of Posterior Collapse in VAEs2025Structured Variational $D$-Decomposition for Accurate and Stable Low-Rank Approximation2025Variational Rank Reduction Autoencoders2025Bidirectional Variational Autoencoders2025CKGAN: Training Generative Adversarial Networks Using Characteristic Kernel Integral Probability Metrics2025Image Interpolation with Score-based Riemannian Metrics of Diffusion Models2025Quantum Down Sampling Filter for Variational Auto-encoder2025LatentGAN Autoencoder: Learning Disentangled Latent Distribution2022MMD GAN: Towards Deeper Understanding of Moment Matching Network2017 · 255 citesAuxiliary Deep Generative Models2016 · 154 citesFlow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models2017 · 74 citesCompressing GANs using Knowledge Distillation2019 · 61 citesFIGR: Few-shot Image Generation with Reptile2019 · 60 citesMonge-Amp\`ere Flow for Generative Modeling2018 · 44 citesLayoutGAN: Generating Graphic Layouts with Wireframe Discriminators2019 · 31 citesMemory Replay GANs: learning to generate images from new categories without forgetting2018 · 30 citesPixelGAN Autoencoders2017 · 25 citesInverting The Generator Of A Generative Adversarial Network2016 · 13 citesDiffusion Causal Models for Counterfactual Estimation2022 · 13 citesWays of Conditioning Generative Adversarial Networks2016 · 12 citesCorrelated discrete data generation using adversarial training2018 · 12 citesVariational Laplace Autoencoders2022 · 12 citesUnbiased Auxiliary Classifier GANs with MINE2020 · 11 citesGenerative Adversarial Network based on Resnet for Conditional Image Restoration2017 · 10 citesLearning the Base Distribution in Implicit Generative Models2018 · 10 citesMultilinear Latent Conditioning for Generating Unseen Attribute Combinations2020 · 7 citesTensorizing Generative Adversarial Nets2017 · 6 citesAnomaly detection with Wasserstein GAN2018 · 6 citesPotential Flow Generator with $L_2$ Optimal Transport Regularity for Generative Models2019 · 6 citesProbabilistic Generative Adversarial Networks2017 · 5 citesWasserstein-Wasserstein Auto-Encoders2019 · 5 citesBayesian Autoencoders: Analysing and Fixing the Bernoulli likelihood for Out-of-Distribution Detection2021 · 5 citesImage Generation and Editing with Variational Info Generative AdversarialNetworks2017 · 3 citesHyperbolic Generative Adversarial Network2021 · 3 citesAlleviating Adversarial Attacks on Variational Autoencoders with MCMC2022 · 3 citesRobust conditional GANs under missing or uncertain labels2019 · 2 citesFIS-GAN: GAN with Flow-based Importance Sampling2019 · 2 citesComparison of Generative Adversarial Networks Architectures Which Reduce Mode Collapse2019 · 2 citesTraining Wasserstein GANs without gradient penalties2021 · 2 citesLifelong Generative Learning via Knowledge Reconstruction2022 · 2 citesA Flexible Diffusion Model2022 · 2 citesUniform Transformation: Refining Latent Representation in Variational Autoencoders2024 · 2 citesEncoder-Powered Generative Adversarial Networks2019 · 1 citesOptimal Transport Based Generative Autoencoders2019 · 1 citesTeaching a GAN What Not to Learn2020 · 1 citesPreventing Oversmoothing in VAE via Generalized Variance Parameterization2021 · 1 citesLearning Robust Variational Information Bottleneck with Reference2021 · 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 citesDeep MMD Gradient Flow without adversarial training2024 · 1 citesOn Kernel-based Variational Autoencoder2024 · 1 citesRank Reduction Autoencoders2024 · 1 citesHierarchical VAE with a Diffusion-based VampPrior2024 · 1 citesLabel-Removed Generative Adversarial Networks Incorporating with K-Means2019Pixel-wise Conditioning of Generative Adversarial Networks2019Conditional Image Generation with One-Vs-All Classifier2020Approximating Probability Distributions by using Wasserstein Generative Adversarial Networks2021Lossless Compression with Latent Variable Models2021EXoN: EXplainable encoder Network2021Feature Alignment as a Generative Process2021Fostering Diversity in Spatial Evolutionary Generative Adversarial Networks2021VAE-CE: Visual Contrastive Explanation using Disentangled VAEs2021An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator2021PIE: Pseudo-Invertible Encoder2021GM Score: Incorporating inter-class and intra-class generator diversity, discriminability of disentangled representation, and sample fidelity for evaluating GANs2021Rotated Digit Recognition by Variational Autoencoders with Fixed Output Distributions2022Visualizing Information Bottleneck through Variational Inference2022Oracle-Preserving Latent Flows2023A Unifying Generator Loss Function for Generative Adversarial Networks2023Score Mismatching for Generative Modeling2023Branched Variational Autoencoder Classifiers2024Short-Time Fourier Transform for deblurring Variational Autoencoders2024Contractive Diffusion Probabilistic Models2024Improved Anomaly Detection through Conditional Latent Space VAE Ensembles2024Analyzing Generative Models by Manifold Entropic Metrics2024Stable Diffusion with Continuous-time Neural Network2024Advancing Diffusion Models: Alias-Free Resampling and Enhanced Rotational Equivariance2024CapsuleGAN: Generative Adversarial Capsule Network2018Generative Models from the perspective of Continual Learning2018Training generative networks using random discriminators2019Hierarchical Mixtures of Generators for Adversarial Learning2019HGAN: Hybrid Generative Adversarial Network2021on the effectiveness of generative adversarial network on anomaly detection2021Training Invertible Neural Networks as Autoencoders2023