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997篇-历史最全生成对抗网络(GAN)论文串烧

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什么是GAN?(本文内容整理自网络)

GAN(Generative Adversarial Netwo,生成对抗网络)是用于无监督学习的机器学习模型,由Ian Goodfellow等人在2014年提出,由神经网络构成判别器和生成器构成,通过一种互相竞争的机制组成的一种学习框架。

 {w:100}{w:100}卷积神经网络之父-Yann LeCun这样评论GAN

在我看来,最重要的是对抗训练( GAN也称为生成对抗网络)。这一想法最初是Ian Goodfellow在蒙特利尔大学读书是提出的,他当时是Yoshua Bengio的学生(Yoshua Bengio先加入了Google Brain,最近有离职加入OpenAI )。在我看来,这一想法与正在被提出的各种变化,是最近十年来在ML中最有趣的想法。

GAN是一个非常强大的框架,这里,我们主要整理了自2014年,GAN推出以来,一些优质的论文,分享给有需要的朋友。

(限于篇幅原因,本文主要列出前50篇GAN相关论文,文末附上完整且带论文链接的list)

列表如下

  1. 3C-GAN: AN CONDITION-CONTEXT-COMPOSITE GENERATIVE ADVERSARIAL NETWORKS FOR GENERATING IMAGES SEPARATELY 2018/1 ICLR2018 3C-GAN

  2. 3D conditional generative adversarial networks for high-quality PET image estimation at low dose

    2018/7 Medical: Reconstruction New

  3. 3D Consistent Biventricular Myocardial Segmentation Using Deep Learning for Mesh Generation

    2018/3 New, 3D

  4. 3D Medical Image Synthesis using Generative Adversarial Networks

    2017/ Medical: Synthersize Medical

  5. 3D Object Reconstruction from a Single Depth View with Adversarial Learning?

    2017/8 Applied Vision 3D-RecGAN

  6. 3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversary Network

    2017/11 ORGAN

  7. 3D Shape Induction from 2D Views of Multiple Objects

    2016/12 3D Object generation PrGAN Citation: 9

  8. 3D-Scene-GAN: Three-dimensional Scene Reconstruction with Generative Adversarial Networks

    2018/2 ICLR2018

  9. A Classification-Based Perspective on GAN Distributions

    2018/1 ICLR2018

  10. A Classification-Based Perspective on GAN Distributions?

    2017/11 Theory & Machine Learning Citation: 1

  11. A conditional adversarial network for semantic segmentation of brain tumor

    2018/2 Medical: Segmentation New

  12. A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models?

    2016/11 Theory & Machine Learning Citation: 16

  13. A Deep Generative Adversarial Architecture for Network-Wide Spatial-Temporal Traffic State Estimation

    2018/1 None

  14. A Deep Predictive Coding Network for Learning Latent Representations

    2018/3 New, Bio

  15. A General Retraining Framework for Scalable Adversarial Classification?

    2016/4 Theory & Machine Learning Citation: 6

  16. A Generalized Active Learning Approach for Unsupervised Anomaly Detection

    2018/5 New

  17. A generative adversarial framework for positive-unlabeled classification

    2017/11 GPU

  18. A Generative Model for Volume Rendering

    2017/10 Medical: Volume Rendering Applied Other

  19. A Hybrid Model for Identity Obfuscation by Face Replacement

    2018/4 New

  20. A Multi-Discriminator CycleGAN for Unsupervised Non-Parallel Speech Domain Adaptation

    2018/4 New

  21. A Novel Approach to Artistic Textual Visualization via GAN?

    2017/10 Applied Vision GAN-ATV

  22. A Self-Training Method for Semi-Supervised GANs

    2018/1 ICLR2018

  23. A Solvable High-Dimensional Model of GAN

    2018/5 New

  24. A step towards procedural terrain generation with GANs?

    2017/7 Applied Vision

  25. A Study into the similarity in generator and discriminator in GAN architecture

    2018/2 None

  26. A Study of Cross-domain Generative Models applied to Cartoon Series?

    2017/9

  27. A survey of image synthesis and editing with generative adversarial networks

  28. A Variational Inequality Perspective on Generative Adversarial Nets

    2018/2 None

  29. A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection?

    2017/4 Object Detection Citation: 12

  30. ABC-GAN: Adaptive Blur and Control for improved training stability of Generative Adversarial Networks

    2017/8 ABC-GAN Stars: 2

  31. Abnormal Event Detection in Videos using Generative Adversarial Nets?

    2017/8 Applied Vision

  32. Accelerated Magnetic Resonance Imaging by Adversarial Neural Network

    2017/9 Medical: Reconstruction

  33. Accelerating Science with?Generative?Adversarial?Networks: An Application to 3D Particle Showers in Multilayer Calorimeters

    2018/1 Medical: Reconstruction New

  34. Activation Maximization Generative Adversarial Nets

    2017/3 Theory & Machine Learning AM-GAN

  35. Activation Maximization Generative Adversarial Nets

    2018/1 ICLR2018

  36. ACtuAL: Actor-Critic Under Adversarial Learning

    2017/11 ACtuAL

  37. AdaGAN: Boosting Generative Models?

    2017/1 Ensemble, Theory & Machine Learning AdaGAN Citation: 19

  38. Adaptive template generation for amyloid PET using a deep learning approach

    2018/5 Medical: Synthersize New

  39. Addressing Challenging Place Recognition Tasks using Generative Adversarial Networks?

    2017/9

  40. Adversarial Attacks on Neural Network Policies?

    2017/2 Citation: 21

  41. Adversarial Autoencoders?

    2015/11 Theory & Machine Learning AAE Citation: 163 Stars: 130

  42. Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data

    2018/3 New

  43. Adversarial Deep Structural Networks for Mammographic Mass Segmentation

    2016/12 BioarXiv

  44. Adversarial Deep Structural Networks for Mammographic Mass Segmentation?

    2016/12 Semantic Segmentation Citation: 7

  45. Adversarial Deep Structured Nets for Mass Segmentation from Mammograms

    2017/10 Medical: Segmentation Stars: 13

  46. Adversarial Discriminative Domain Adaptation?

    2017/2 Theory & Machine Learning Citation: 52

  47. Adversarial examples for generative models

    2017/2 Adversarial Examples (Defense vs Attack)

  48. Adversarial Examples for Semantic Segmentation and Object Detection?

    2017/7 Citation: 17

  49. Adversarial Examples Generation and Defense Based on Generative Adversarial Network

    2017/ Adversarial Examples (Defense vs Attack)

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机器学习模型神经网络
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