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生成对抗网络 (Generative Adversarial Network, GAN) 是一类神经网络，通过轮流训练判别器 (Discriminator) 和生成器 (Generator)，令其相互对抗，来从复杂概率分布中采样，例如生成图片、文字、语音等。GAN 最初由 Ian Goodfellow 提出，原论文见 Generative Adversarial Networks
PGMEL: Policy Gradient-based Generative Adversarial Network for Multimodal Entity Linking
Arxiv
0+阅读 · 10月3日
Mutual information maximizing quantum generative adversarial networks
Arxiv
0+阅读 · 10月1日
From Satellite to Street: A Hybrid Framework Integrating Stable Diffusion and PanoGAN for Consistent Cross-View Synthesis
Arxiv
0+阅读 · 9月29日
Style transfer between Microscopy and Magnetic Resonance Imaging via Generative Adversarial Network in small sample size settings
Arxiv
0+阅读 · 8月12日
Learning Kinetic Monte Carlo stochastic dynamics with Deep Generative Adversarial Networks
Arxiv
0+阅读 · 7月29日
Generative Adversarial Networks Applied for Privacy Preservation in Biometric-Based Authentication and Identification
Arxiv
0+阅读 · 9月24日
Determination of galaxy photometric redshifts using Conditional Generative Adversarial Networks (CGANs)
Arxiv
0+阅读 · 7月17日
Determination of galaxy photometric redshifts using Conditional Generative Adversarial Networks (CGANs)
Arxiv
0+阅读 · 3月13日
Deep learning-based filtering of cross-spectral matrices using generative adversarial networks
Arxiv
0+阅读 · 2月28日
HiFi-Stream: Streaming Speech Enhancement with Generative Adversarial Networks
Arxiv
0+阅读 · 3月21日
RainScaleGAN: a Conditional Generative Adversarial Network for Rainfall Downscaling
Arxiv
0+阅读 · 3月17日
Rates of convergence for nonparametric estimation of singular distributions using generative adversarial networks
Arxiv
0+阅读 · 2月27日
SPDGAN: A Generative Adversarial Network based on SPD Manifold Learning for Automatic Image Colorization
Arxiv
0+阅读 · 2月25日
Investigating Parameter-Efficiency of Hybrid QuGANs Based on Geometric Properties of Generated Sea Route Graphs
Arxiv
0+阅读 · 1月27日
Generative Adversarial Networks Bridging Art and Machine Intelligence
Arxiv
0+阅读 · 2月6日
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