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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
Cluster Aggregated GAN (CAG): A Cluster-Based Hybrid Model for Appliance Pattern Generation
Arxiv
0+阅读 · 6月11日
A Residual Guided strategy with Generative Adversarial Networks in training Physics-Informed Transformer Networks
Arxiv
0+阅读 · 4月2日
Diffusion-Guided Adversarial Perturbation Injection for Generalizable Defense Against Facial Manipulations
Arxiv
0+阅读 · 4月2日
Well Log-Guided Synthesis of Subsurface Images from Sparse Petrography Data Using cGANs
Arxiv
0+阅读 · 3月10日
Context-free Self-Conditioned GAN for Trajectory Forecasting
Arxiv
0+阅读 · 3月9日
DiffusionXRay: A Diffusion and GAN-Based Approach for Enhancing Digitally Reconstructed Chest Radiographs
Arxiv
0+阅读 · 3月2日
Condition Matters in Full-head 3D GANs
Arxiv
0+阅读 · 2月6日
Facial Recognition Leveraging Generative Adversarial Networks
Arxiv
0+阅读 · 1月31日
Bridging GANs and Bayesian Neural Networks via Partial Stochasticity
Arxiv
0+阅读 · 2月1日
Physically Plausible Multi-System Trajectory Generation and Symmetry Discovery
Arxiv
0+阅读 · 1月14日
SGW-GAN: Sliced Gromov-Wasserstein Guided GANs for Retinal Fundus Image Enhancement
Arxiv
0+阅读 · 1月19日
Sim-to-Real Transfer via a Style-Identified Cycle Consistent Generative Adversarial Network: Zero-Shot Deployment on Robotic Manipulators through Visual Domain Adaptation
Arxiv
0+阅读 · 1月23日
IGAN: A New Inception-based Model for Stable and High-Fidelity Image Synthesis Using Generative Adversarial Networks
Arxiv
0+阅读 · 1月13日
Generative Adversarial Networks for Image Super-Resolution: A Survey
Arxiv
0+阅读 · 1月13日
Logic Tensor Network-Enhanced Generative Adversarial Network
Arxiv
0+阅读 · 1月7日
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