Methods › Computer Vision › Generative Adversarial Networks › InfoGAN
InfoGAN
Introduced by Xi Chen et al. in InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
InfoGAN is a type of generative adversarial network that modifies the GAN objective to encourage it to learn interpretable and meaningful representations. This is done by maximizing the mutual information between a fixed small subset of the GAN’s noise variables and the observations.
Formally, InfoGAN is defined as a minimax game with a variational regularization of mutual information and the hyperparameter λ:
min_(G, Q)max_DV_(INFOGAN)(D, G, Q) = V(D, G) - λL_I(G, Q)
Where Q is an auxiliary distribution that approximates the posterior P(c|x) - the probability of the latent code c given the data x - and L_I is the variational lower bound of the mutual information between the latent code and the observations.
In the practical implementation, there is another fully-connected layer to output parameters for the conditional distribution Q (negligible computation ontop of regular GAN structures). Q is represented with a softmax non-linearity for a categorical latent code. For a continuous latent code, the authors assume a factored Gaussian.
Papers archive 2025-07-28
30 shown of 35, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Generative Adversarial Networks Bridging Art and Machine Intelligence 6 Feb 2025 · 0 repositories · arXiv:2502.04116
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Unsupervised and Interpretable Synthesizing for Electrical Time Series Based on Information Maximizing Generative Adversarial Nets 18 Jul 2024 · 0 repositories · arXiv:2407.13691
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Comparing the information content of probabilistic representation spaces 31 May 2024 · 1 repository · arXiv:2405.21042
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Double InfoGAN for Contrastive Analysis 31 Jan 2024 · 1 repository · arXiv:2401.17776
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GAN-GA: A Generative Model based on Genetic Algorithm for Medical Image Generation 30 Dec 2023 · 0 repositories · arXiv:2401.00314
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Fusing Conditional Submodular GAN and Programmatic Weak Supervision 16 Dec 2023 · 1 repository · arXiv:2312.10366Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
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The objective function equality property of infoGAN for two-layer network 30 Sep 2023 · 0 repositories · arXiv:2310.00443
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HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by Maximising Approximated Mutual Information 6 Aug 2022 · 1 repository · arXiv:2208.03563
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k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension 17 Jun 2022 · 0 repositories · arXiv:2206.08526
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Analytical Interpretation of Latent Codes in InfoGAN with SAR Images 26 May 2022 · 0 repositories · arXiv:2205.13294
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LatentGAN Autoencoder: Learning Disentangled Latent Distribution 5 Apr 2022 · 0 repositories · arXiv:2204.02010
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Contrastive Fine-grained Class Clustering via Generative Adversarial Networks 30 Dec 2021 · 1 repository · arXiv:2112.14971Syntology ran 0 of 3 samples · 3 unverified · 3 pointer-only (licence)
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Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey 26 Nov 2021 · 0 repositories · arXiv:2111.13282
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Inference-InfoGAN: Inference Independence via Embedding Orthogonal Basis Expansion 2 Oct 2021 · 0 repositories · arXiv:2110.00788
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ADIS-GAN: Affine Disentangled GAN 1 Jan 2021 · 0 repositories
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Representation Decomposition for Image Manipulation and Beyond 2 Nov 2020 · 0 repositories · arXiv:2011.00788
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DPD-InfoGAN: Differentially Private Distributed InfoGAN 22 Oct 2020 · 0 repositories · arXiv:2010.11398
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CiwGAN and fiwGAN: Encoding information in acoustic data to model lexical learning with Generative Adversarial Networks 4 Jun 2020 · 1 repository · arXiv:2006.02951
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Disentanglement based Active Learning 15 Dec 2019 · 1 repository · arXiv:1912.07018
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Towards Better Understanding of Disentangled Representations via Mutual Information 25 Nov 2019 · 0 repositories · arXiv:1911.10922
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Generative Adversarial Networks for Failure Prediction 4 Oct 2019 · 0 repositories · arXiv:1910.02034
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Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data 1 Oct 2019 · 1 repository · arXiv:1910.01112
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Generating Geological Facies Models with Fidelity to Diversity and Statistics of Training Images using Improved Generative Adversarial Networks 23 Sep 2019 · 0 repositories · arXiv:1909.10652
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Maximizing Mutual Information for Tacotron 30 Aug 2019 · 2 repositories · arXiv:1909.01145
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Unsupervised Classification of Street Architectures Based on InfoGAN 30 May 2019 · 0 repositories · arXiv:1905.12844
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Learning Robotic Manipulation through Visual Planning and Acting 11 May 2019 · 0 repositories · arXiv:1905.04411
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IB-GAN: Disentangled Representation Learning with Information Bottleneck GAN 1 May 2019 · 2 repositories
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Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs 20 Apr 2019 · 1 repository · arXiv:1904.09507
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Heartbeat Anomaly Detection using Adversarial Oversampling 28 Jan 2019 · 1 repository · arXiv:1901.09972
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Classification of sparsely labeled spatio-temporal data through semi-supervised adversarial learning 26 Jan 2018 · 0 repositories · arXiv:1801.08712
Tasks archive 2025-07-28
20 shown of 50 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
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Categories archive 2025-07-28
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