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Paper Citation Record · LEDGER

Generative Adversarial Networks Bridging Art and Machine Intelligence

As of 9 August 2026, this Paper Citation Record lists 100 of 229 outbound references and 0 inbound Pith citation observations for arXiv:2502.04116.

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pith.paper-citation-record.v1
2502.04116 v2

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measured 100 of 229 reference resolution

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

100 of 229 outbound references displayed

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Outbound references

Observation de1cf02c-81b4-4999-bb47-20415c9e2a7b · outbound

This paper cites Generative adversarial networks,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Generative adversarial networks,

Reference 1

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This paper cites Generative adversarial networks: An overview,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Generative adversarial networks: An overview,

Reference 2

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This paper cites Unrolled Generative Adversarial Networks.

Generative Adversarial Networks Bridging Art and Machine Intelligence Unrolled Generative Adversarial Networks

Reference 3

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Observation d3ddbf55-f685-4bfe-b6aa-9d1614c3ef89 · outbound

This paper cites Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.

Generative Adversarial Networks Bridging Art and Machine Intelligence Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

Reference 4

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This paper cites Coupled generative adversarial networks,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Coupled generative adversarial networks,

Reference 5

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This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

Generative Adversarial Networks Bridging Art and Machine Intelligence Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 6

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This paper cites A style-based generator architecture for generative adversarial networks,.

Generative Adversarial Networks Bridging Art and Machine Intelligence A style-based generator architecture for generative adversarial networks,

Reference 7

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Observation acbaa909-25ef-447e-a73d-a2d01fafaafc · outbound

This paper cites Isfb-gan: Interpretable semantic face beautification with generative adversarial network,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Isfb-gan: Interpretable semantic face beautification with generative adversarial network,

Reference 8

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Observation f49ef4d6-49c2-448c-965c-ac361d6df234 · outbound

This paper cites Generative adversarial networks: introduction and outlook,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Generative adversarial networks: introduction and outlook,

Reference 9

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This paper cites Generative adversarial network: An overview of theory and applications,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Generative adversarial network: An overview of theory and applications,

Reference 10

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This paper cites A review on generative adversarial networks: Algorithms, theory, and applications,.

Generative Adversarial Networks Bridging Art and Machine Intelligence A review on generative adversarial networks: Algorithms, theory, and applications,

Reference 11

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This paper cites Wasserstein generative adversarial networks,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Wasserstein generative adversarial networks,

Reference 12

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Observation 11754c4d-7c84-4b0a-81c0-08bbdd3280d8 · outbound

This paper cites Semantic image synthesis with spatially-adaptive normalization,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Semantic image synthesis with spatially-adaptive normalization,

Reference 13

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Observation dca824d2-5b15-4481-a34a-aead1e83f60e · outbound

This paper cites Large Scale GAN Training for High Fidelity Natural Image Synthesis.

Generative Adversarial Networks Bridging Art and Machine Intelligence Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 14

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Generative Adversarial Networks Bridging Art and Machine Intelligence Analyzing and improving the image quality of stylegan,

Reference 15

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Generative Adversarial Networks Bridging Art and Machine Intelligence Alias-free genera- tive adversarial networks,

Reference 16

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Generative Adversarial Networks Bridging Art and Machine Intelligence Scaling up gans for text-to-image synthesis,

Reference 17

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Generative Adversarial Networks Bridging Art and Machine Intelligence Sparse-gan: Sparsity- constrained generative adversarial network for anomaly detection in retinal oct image,

Reference 18

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Generative Adversarial Networks Bridging Art and Machine Intelligence Auto-Encoding Variational Bayes

Reference 19

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Generative Adversarial Networks Bridging Art and Machine Intelligence An introduction to variational autoencoders,

Reference 20

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Generative Adversarial Networks Bridging Art and Machine Intelligence A learning algorithm for boltzmann machines,

Reference 21

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Generative Adversarial Networks Bridging Art and Machine Intelligence Rectified linear units improve restricted boltzmann machines,

Reference 22

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Generative Adversarial Networks Bridging Art and Machine Intelligence A probability distribution and its uses in fitting data,

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Generative Adversarial Networks Bridging Art and Machine Intelligence Dimensionality reduction: A com- parative review,

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Generative Adversarial Networks Bridging Art and Machine Intelligence Why does unsupervised pre-training help deep learning?,

Reference 25

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Generative Adversarial Networks Bridging Art and Machine Intelligence Elbo surgery: yet another way to carve up the variational evidence lower bound,

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Generative Adversarial Networks Bridging Art and Machine Intelligence Statistical analysis based on a certain multivariate complex gaussian distribu- tion (an introduction),

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Generative Adversarial Networks Bridging Art and Machine Intelligence Latent space approaches to social network analy- sis,

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Generative Adversarial Networks Bridging Art and Machine Intelligence Gans for medical image analysis,

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Generative Adversarial Networks Bridging Art and Machine Intelligence Pytorch: An imperative style, high-performance deep learning library,

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Generative Adversarial Networks Bridging Art and Machine Intelligence Stevens, L

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Generative Adversarial Networks Bridging Art and Machine Intelligence Kottwitz, LaTeX Graphics with TikZ: A practitioner’s guide to drawing 2D and 3D images, dia- grams, charts, and plots

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Generative Adversarial Networks Bridging Art and Machine Intelligence The real-world-weight cross-entropy loss function: Modeling the costs of mislabeling,

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Generative Adversarial Networks Bridging Art and Machine Intelligence Approximations to the log-likelihood function in the nonlinear mixed-effects model,

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Generative Adversarial Networks Bridging Art and Machine Intelligence An analysis of edge detection by using the jensen-shannon divergence,

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Generative Adversarial Networks Bridging Art and Machine Intelligence Approximating the kullback leibler divergence between gaus- sian mixture models,

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Generative Adversarial Networks Bridging Art and Machine Intelligence Veegan: Reducing mode collapse in gans using implicit variational learning,

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Generative Adversarial Networks Bridging Art and Machine Intelligence Catastrophic forgetting and mode collapse in gans,

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Generative Adversarial Networks Bridging Art and Machine Intelligence The vanishing gradient problem during learning recurrent neural nets and problem solutions,

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Observation 87b19e98-1eac-4ce3-bcdc-6ad227affcff · outbound

This paper cites Which neural net architectures give rise to exploding and vanishing gradients?,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Which neural net architectures give rise to exploding and vanishing gradients?,

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Observation a93f72b1-a2a9-47d3-b503-4098571771c0 · outbound

This paper cites When does label smoothing help?,.

Generative Adversarial Networks Bridging Art and Machine Intelligence When does label smoothing help?,

Reference 41

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Observation 03a691e7-37eb-4bd3-8790-032113ff169d · outbound

This paper cites How does batch normalization help optimiza- tion?,.

Generative Adversarial Networks Bridging Art and Machine Intelligence How does batch normalization help optimiza- tion?,

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Observation 0b365993-2394-49a2-adcd-ba3946e9e039 · outbound

This paper cites Understanding batch normalization,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Understanding batch normalization,

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Observation 1f158b3b-c787-4c8b-9873-b79dd71827cb · outbound

This paper cites Learning with a wasserstein loss,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Learning with a wasserstein loss,

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source=pdf_text observed=2026-08-08T23:30:58.907571Z digest=sha256:f0a0cf3303a162f738a8f5188f7a5af262dfb31fb4864d2d55127d647e8eb3cf

Observation ede03d5b-cf5e-4d94-a28d-e7d54bf56fdb · outbound

This paper cites Probgan: Towards probabilistic gan with theoretical guarantees,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Probgan: Towards probabilistic gan with theoretical guarantees,

Reference 45

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source=pdf_text observed=2026-08-08T23:30:58.910676Z digest=sha256:56baadd598952002cb63b66612cc1c0dee59161dcd963e921f365495908ab7e5

Observation 13224f7e-9526-4fcc-a413-72ffd7d8fb13 · outbound

This paper cites Seeing what a gan cannot generate,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Seeing what a gan cannot generate,

Reference 46

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source=pdf_text observed=2026-08-08T23:30:58.913640Z digest=sha256:a2796807c7fc3d719bf3a173d512567763731806a5b766f49aa762e3b4075358

Observation 65c9d9fd-e111-4d53-be0b-e370fdc7770e · outbound

This paper cites Must-gan: Multi-level statistics transfer for self-driven person image generation,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Must-gan: Multi-level statistics transfer for self-driven person image generation,

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source=pdf_text observed=2026-08-08T23:30:58.916689Z digest=sha256:df4078eebba07269ceedc0476175a89ea403be71f349bb0027cd062f9c1f4866

Observation b6925e66-f123-450a-bce9-ed7b04b59942 · outbound

This paper cites Fudenberg and J.

Generative Adversarial Networks Bridging Art and Machine Intelligence Fudenberg and J

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source=pdf_text observed=2026-08-08T23:30:58.919749Z digest=sha256:1b362886acd0bedc18d6a87a5185bb379e8eb6811e6622c4b03e8aa27399929b

Observation 7f9a46eb-86d1-4163-b94b-ea4b1a41c446 · outbound

This paper cites The complexity of computing a nash equilibrium,.

Generative Adversarial Networks Bridging Art and Machine Intelligence The complexity of computing a nash equilibrium,

Reference 49

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source=pdf_text observed=2026-08-08T23:30:58.922888Z digest=sha256:5bea9195ca3deffe9f25ded17d603e49c7e69c5b509dfd319e1b70c51af46bd2

Observation 5a1c139d-5f42-462d-bdcf-928a6e76efe5 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Gans trained by a two time-scale update rule converge to a local nash equilibrium,

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source=pdf_text observed=2026-08-08T23:30:58.926139Z digest=sha256:a5155f6cfc89f770eabd3ea0679f4d5a86c57e21ac672e6877e28a944a5381e0

Observation fbdc4f08-3434-4797-b930-b1888a8cb642 · outbound

This paper cites Do gans always have nash equilibria?,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Do gans always have nash equilibria?,

Reference 51

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source=pdf_text observed=2026-08-08T23:30:58.929362Z digest=sha256:55790f1fe0bc28a7cf195a2b3a8130c0526cc8dfe13c1e070092da62b112f28c

Observation 0832c7ee-171a-4da8-8e36-00e67eb56c20 · outbound

This paper cites On estimation of a probability density function and mode,.

Generative Adversarial Networks Bridging Art and Machine Intelligence On estimation of a probability density function and mode,

Reference 52

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source=pdf_text observed=2026-08-08T23:30:58.932632Z digest=sha256:f80ab788eaabad684d8f557b1842eaac5e70dec752422133df9fd873b72fa3bf

Observation ec9adb61-fc24-453d-9e41-aec3eb4baa7b · outbound

This paper cites Bayesian gan,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Bayesian gan,

Reference 53

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source=pdf_text observed=2026-08-08T23:30:58.935858Z digest=sha256:3fb59b5fdb7650b217962304789c6d27badeac2eaeb64718d88005ddad33633c

Observation 60a45e1e-4f11-43b8-ac94-6cf41b9eba50 · outbound

This paper cites Kuipers and H.

Generative Adversarial Networks Bridging Art and Machine Intelligence Kuipers and H

Reference 54

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source=pdf_text observed=2026-08-08T23:30:58.939584Z digest=sha256:9eb71ac5868c074f09c5784faec9d644b5c84ef70dc6867c4ab27d7b534720c6

Observation f0c06dc6-c772-48a4-800b-9ee29fd6496d · outbound

This paper cites The jensen-shannon divergence,.

Generative Adversarial Networks Bridging Art and Machine Intelligence The jensen-shannon divergence,

Reference 55

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source=pdf_text observed=2026-08-08T23:30:58.942846Z digest=sha256:a81572c39b9b0b05048abdc0ad36f5252e37e940d033c98bf1520d028a1e9076

Observation eb1e9eb6-8f57-40a0-b7c4-609cbc349839 · outbound

This paper cites Jensen-shannon divergence and hilbert space embedding,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Jensen-shannon divergence and hilbert space embedding,

Reference 56

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source=pdf_text observed=2026-08-08T23:30:58.945890Z digest=sha256:f0d3f9bc6d1dc09dc1e5cd7b3195003b34c91bf6221f1a1649c3a8197a5488eb

Observation 783b5a80-acb5-4a0f-8f76-9c79c85b44fa · outbound

This paper cites Work and life: The end of the zero-sum game,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Work and life: The end of the zero-sum game,

Reference 57

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source=pdf_text observed=2026-08-08T23:30:58.949440Z digest=sha256:0dc6a98cc9290613feae25f2133fd129d48f7d83db03ba61086ce192925a5db8

Observation e05ef2b8-578d-4814-afbb-cd37b99fcf24 · outbound

This paper cites Quiñonero-Candela, M.

Generative Adversarial Networks Bridging Art and Machine Intelligence Quiñonero-Candela, M

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Observation 0fc261eb-ac53-4209-9725-0b124a68b859 · outbound

This paper cites Gradient-based learning applied to document recognition,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Gradient-based learning applied to document recognition,

Reference 59

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source=pdf_text observed=2026-08-08T23:30:58.956088Z digest=sha256:bba50bb7aef7447785c0574016079c573cbcfeed7932fb4e9030bd1e63e689aa

Observation 3ab1eb03-6eb5-42cf-ac6b-3d228bf8bb20 · outbound

This paper cites Binary cross entropy with deep learning technique for image classi- fication,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Binary cross entropy with deep learning technique for image classi- fication,

Reference 60

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source=pdf_text observed=2026-08-08T23:30:58.959349Z digest=sha256:e69aa28161a0d58569ad0c1d6c5dc0e36690f4d826e9455fb39c6ea58fe68f30

Observation ef96405d-48ec-4311-902c-4347f6f4b214 · outbound

This paper cites The earth mover’s distance as a metric for image re- trieval,.

Generative Adversarial Networks Bridging Art and Machine Intelligence The earth mover’s distance as a metric for image re- trieval,

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source=pdf_text observed=2026-08-08T23:30:58.962470Z digest=sha256:c945310f4688d82b7d45191725e098d14bdb7de1f9e922c9910a48b8a4eedf39

Observation 6c1a2987-561e-4026-8d6f-b0263f64a6d0 · outbound

This paper cites Dimension-wise importance sampling weight clipping for sample-efficient reinforcement learning,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Dimension-wise importance sampling weight clipping for sample-efficient reinforcement learning,

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source=pdf_text observed=2026-08-08T23:30:58.965535Z digest=sha256:c08666855dc2f6ca0a3b76844d33e64e2a429ad06b24ed7cba89011b71e9c878

Observation fcf21677-ff28-48d4-9f1e-24e8dbacde2d · outbound

This paper cites Weight Clipping for Deep Continual and Reinforcement Learning.

Generative Adversarial Networks Bridging Art and Machine Intelligence Weight Clipping for Deep Continual and Reinforcement Learning

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source=pdf_text observed=2026-08-08T23:30:58.968601Z digest=sha256:0943f835f72abed8f06e52c4f183863cf5f80a1cf6c1481f661c446a886028ea

Observation ea661d1f-7542-482f-9f7e-3267167f4bec · outbound

This paper cites Preventing gradient attenua- tion in lipschitz constrained convolutional networks,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Preventing gradient attenua- tion in lipschitz constrained convolutional networks,

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source=pdf_text observed=2026-08-08T23:30:58.972136Z digest=sha256:1f9d11e09c8297db793912cd01275f5d55598920b911d85f6aefefee2e590799

Observation 84ac0b35-1f31-430a-bd36-61a3e345b9e5 · outbound

This paper cites Linear hinge loss and average margin,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Linear hinge loss and average margin,

Reference 65

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source=pdf_text observed=2026-08-08T23:30:58.975794Z digest=sha256:538045670245bf015397aa4334a71e42eaae1a5a82a8b2581cc980c4934f7a25

Observation 7aa1640e-7adb-4802-96bc-85a7f4238ca8 · outbound

This paper cites Classification with a reject option using a hinge loss.,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Classification with a reject option using a hinge loss.,

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source=pdf_text observed=2026-08-08T23:30:58.979917Z digest=sha256:a7e3951e4d22694cf28273a53e090b19de58339185d5d8aebb0812e7565d9093

Observation edbb156b-fb68-43e2-a0af-e5b9182b4d57 · outbound

This paper cites Self-attention generative adversarial net- works,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Self-attention generative adversarial net- works,

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source=pdf_text observed=2026-08-08T23:30:58.983198Z digest=sha256:0f371a09175ec1e8278cebafb9254d63a25830391eef162bd6e8c38405617a34

Observation 7a5779cd-d179-4904-b852-6c6117280b69 · outbound

This paper cites Conditional Generative Adversarial Nets.

Generative Adversarial Networks Bridging Art and Machine Intelligence Conditional Generative Adversarial Nets

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source=pdf_text observed=2026-08-08T23:30:58.986228Z digest=sha256:b6eda577de96d8d37e7b2c2129fd336476825a826f59f8ea09de629ee276505e

Observation a38bca1e-203d-4c27-bd65-676ec0ce7b31 · outbound

This paper cites High-resolution image syn- thesis and semantic manipulation with conditional gans,.

Generative Adversarial Networks Bridging Art and Machine Intelligence High-resolution image syn- thesis and semantic manipulation with conditional gans,

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source=pdf_text observed=2026-08-08T23:30:58.989762Z digest=sha256:d5e7d1b059d73d9ee6771b8bad201f0438f1dbbe784dd7f8884c5841d4582b26

Observation 8cdf38dc-bc26-4935-8087-5e7fad78de77 · outbound

This paper cites Gan compression: Efficient architectures for interactive conditional gans,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Gan compression: Efficient architectures for interactive conditional gans,

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source=pdf_text observed=2026-08-08T23:30:58.993088Z digest=sha256:4c56e181d7f7c8277778210cf17c6a379d877dca36931b5f7a70d1050e509f2b

Observation 2c7bf41c-26fe-4804-9476-3d36d84b8b14 · outbound

This paper cites On the Evaluation of Conditional GANs.

Generative Adversarial Networks Bridging Art and Machine Intelligence On the Evaluation of Conditional GANs

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T23:30:58.996016Z digest=sha256:1b59274e179f3496cf63d368379fb93bc66ae9ef7a211d203db950caf37342ae

Observation 0666b9b6-1fe8-49dc-a4bf-60ae5f7db761 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research [best of the web],.

Generative Adversarial Networks Bridging Art and Machine Intelligence The mnist database of handwritten digit images for machine learning research [best of the web],

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source=pdf_text observed=2026-08-08T23:30:58.999178Z digest=sha256:408fc5a22170716dfd7b7971c891e2fb765e0766dd9f660a8c4107e14eb1f362

Observation c9e81b87-6ffd-4f5b-b42f-d8afe7acf844 · outbound

This paper cites Robustness of conditional gans to noisy labels,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Robustness of conditional gans to noisy labels,

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source=pdf_text observed=2026-08-08T23:30:59.002320Z digest=sha256:fd63758f7af331c563383c0ee89d4af784281f3a6c63e17d18e4a57891010543

Observation e261da48-3951-4e66-9237-65983ea7dccf · outbound

This paper cites Cvae-gan: fine-grained image generation through asymmetric training,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Cvae-gan: fine-grained image generation through asymmetric training,

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source=pdf_text observed=2026-08-08T23:30:59.005161Z digest=sha256:fc4fa787aa8e054ceacafed14fc090666ad953d98d82c5a999c348eaedfca98f

Observation dda4c3e2-8ada-4c4a-b903-1991005b7cfd · outbound

This paper cites Multi-scale multi-class conditional generative ad- versarial network for handwritten character generation,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Multi-scale multi-class conditional generative ad- versarial network for handwritten character generation,

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source=pdf_text observed=2026-08-08T23:30:59.008711Z digest=sha256:ee93875b1c2ccd94916667261b8fd0d980bf993c2b669c0c0817f76358605134

Observation 198587bb-6b1c-495b-b245-058e1b2652b4 · outbound

This paper cites Dualgan: Unsupervised dual learning for image-to-image translation,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Dualgan: Unsupervised dual learning for image-to-image translation,

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source=pdf_text observed=2026-08-08T23:30:59.011934Z digest=sha256:6d906b031fa2f76194714ae48fd7083e2f40646f693f3876068809397d537f94

Observation 8c038a51-02f7-4f87-b35e-91c9edf94477 · outbound

This paper cites A case study of conditional deep convolutional generative adversarial networks in machine fault diagnosis,.

Generative Adversarial Networks Bridging Art and Machine Intelligence A case study of conditional deep convolutional generative adversarial networks in machine fault diagnosis,

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Observation f4ffc3b5-4ddd-4c52-9b0a-78b0d2badfd5 · outbound

This paper cites Deep learning,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Deep learning,

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source=pdf_text observed=2026-08-08T23:30:59.018031Z digest=sha256:b386f83651d743d20bfbaff1e1eccb28133b7f63cc835c20c6f6a0ae163d5de4

Observation 643f0cf4-97f6-4df3-aa6e-93b32360d358 · outbound

This paper cites An Introduction to Convolutional Neural Networks.

Generative Adversarial Networks Bridging Art and Machine Intelligence An Introduction to Convolutional Neural Networks

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source=pdf_text observed=2026-08-08T23:30:59.021330Z digest=sha256:3a1c06a253fb65b3348dd3b4547616e540ed57516e67b79ef071608f657d57a4

Observation e1d6848b-b192-4af0-a1f4-e43012a88e2e · outbound

This paper cites Comparative study of convolution neural networkâĂŹs relu and leaky- relu activation functions,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Comparative study of convolution neural networkâĂŹs relu and leaky- relu activation functions,

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Observation b3bd6c90-1e81-461b-b798-d78c62b61692 · outbound

This paper cites an unresolved cited work.

Generative Adversarial Networks Bridging Art and Machine Intelligence Unresolved cited work

Reference 81

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Observation f8b04480-ef1a-4396-a610-c922f4cf6030 · outbound

This paper cites Infogan: Interpretable representation learning by information maximizing generative adversarial nets,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Infogan: Interpretable representation learning by information maximizing generative adversarial nets,

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Observation 7d5f7110-610c-4f68-8907-699ad51ff4c4 · outbound

This paper cites Learning plannable representations with causal infogan,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Learning plannable representations with causal infogan,

Reference 83

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Observation 3e008208-a2c4-421e-96d4-5178f89ed462 · outbound

This paper cites Dpd-infogan: Differentially private distributed infogan,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Dpd-infogan: Differentially private distributed infogan,

Reference 84

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Observation c1d55afc-57ac-4bb7-af9e-39db6e5ca957 · outbound

This paper cites Deep generative image models using aï£ij laplacian pyramid of adversarial networks,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Deep generative image models using aï£ij laplacian pyramid of adversarial networks,

Reference 85

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Observation 8423eced-8b22-476c-9d46-1a8d1b09f647 · outbound

This paper cites Hierarchical generation of molecular graphs using structural motifs,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Hierarchical generation of molecular graphs using structural motifs,

Reference 86

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Observation 2d7b74c0-0957-42f8-b47b-63ea54a43150 · outbound

This paper cites Photographic text-to-image synthesis with a hierarchically-nested adversarial network,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Photographic text-to-image synthesis with a hierarchically-nested adversarial network,

Reference 87

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Observation e921f0fc-bf45-4095-a8f0-b6810ec4f2a7 · outbound

This paper cites Grarep: Learning graph representations with global structural informa- tion,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Grarep: Learning graph representations with global structural informa- tion,

Reference 88

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source=pdf_text observed=2026-08-08T23:30:59.053873Z digest=sha256:8aafe3c5862e574e8db85aa311741d4e7f6b2640019e5e87e439b36eb36e18bb

Observation a34f577b-6bdb-470e-8500-8e6ef21d2fb7 · outbound

This paper cites Fast and accurate image super-resolution with deep laplacian pyramid networks,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Fast and accurate image super-resolution with deep laplacian pyramid networks,

Reference 89

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source=pdf_text observed=2026-08-08T23:30:59.057713Z digest=sha256:486e66afd1a8cafe5a4085237f8abe3d306aaffa44c6f0e4fdf8fcfc4640e070

Observation 176edb78-4441-4806-9d84-4bf00fb9541f · outbound

This paper cites Which training methods for gans do actually con- verge?,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Which training methods for gans do actually con- verge?,

Reference 90

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source=pdf_text observed=2026-08-08T23:30:59.061372Z digest=sha256:fbefa67d49dd533b0d748b01f9f8de7b3652abc18b2069689615202ecbb3546b

Observation 0fbc7216-baed-4c03-a862-2454c742e385 · outbound

This paper cites Instability and local minima in gan training with kernel discriminators,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Instability and local minima in gan training with kernel discriminators,

Reference 91

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source=pdf_text observed=2026-08-08T23:30:59.064607Z digest=sha256:76dc986b99dfa28befb7c43c359dee757f023e9f071fda4bfad43fc195177ba4

Observation fa73d6f7-86f0-4536-b18c-1494d8cd73e4 · outbound

This paper cites Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues.

Generative Adversarial Networks Bridging Art and Machine Intelligence Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues

Reference 92

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Observation 06abbb64-7d35-4afd-9713-1cd53f4d445f · outbound

This paper cites Take a close look at mode collapse and vanishing gradient in gan,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Take a close look at mode collapse and vanishing gradient in gan,

Reference 93

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source=pdf_text observed=2026-08-08T23:30:59.071620Z digest=sha256:f4ae197e77a1c9bdee53ef2e0f73f529f3c3aacb32abd3e5fb7d7e14d9a2f413

Observation cd8995b1-1836-4762-8ba1-b4fe7abd1e39 · outbound

This paper cites Mode collapse in generative adversarial networks: An overview,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Mode collapse in generative adversarial networks: An overview,

Reference 94

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Observation 6c1df40f-43ab-4733-961e-c7341d95489a · outbound

This paper cites Banach wasserstein gan,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Banach wasserstein gan,

Reference 95

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source=pdf_text observed=2026-08-08T23:30:59.078297Z digest=sha256:5709c30382ea1cf2c25ca9e947ba5957574bbef07c0b08fa8066c54882279081

Observation 4ae30cc8-d48e-40d8-a40a-c96ec5e7991b · outbound

This paper cites Improved training of wasser- stein gans,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Improved training of wasser- stein gans,

Reference 96

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source=pdf_text observed=2026-08-08T23:30:59.082167Z digest=sha256:62a6370adc262d28fd4b06bfd3cd3af870eb2cf7d7b45a4baae498960c58b68d

Observation 561954c5-a9a9-458a-9989-743a4c12c134 · outbound

This paper cites Least squares generative adversarial networks,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Least squares generative adversarial networks,

Reference 97

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source=pdf_text observed=2026-08-08T23:30:59.085810Z digest=sha256:b80e0bcf90da4060cd3174617e1ef15c17ec300497a82df9b4fe3477723be3d7

Observation 7c4c34d1-b8de-41ca-ba51-65994e428a9f · outbound

This paper cites Sorting out lipschitz function approximation,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Sorting out lipschitz function approximation,

Reference 98

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source=pdf_text observed=2026-08-08T23:30:59.089747Z digest=sha256:ce78c8f79310e162d033251e83e596cbfd45fe8def59010fe845f4029195ed9a

Observation d6c3eed7-95be-4d20-b77e-e230304f986d · outbound

This paper cites Least squares generative adversarial networks-based anomaly detection,.

Generative Adversarial Networks Bridging Art and Machine Intelligence Least squares generative adversarial networks-based anomaly detection,

Reference 99

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Observation 5d84b98c-c513-4e2c-9e1c-4eff6e56b0a3 · outbound

This paper cites Spectral Normalization for Generative Adversarial Networks.

Generative Adversarial Networks Bridging Art and Machine Intelligence Spectral Normalization for Generative Adversarial Networks

Reference 100

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Pith citing papers

No inbound Pith citation observations are available.