Latest Research in Generative Adversarial Networks and Image Synthesis

Top Research Topics in Generative Adversarial Networks and Image Synthesis

• Machine Learning — 44 papers
• Generative Adversarial Networks and Image Synthesis — 6 papers
• Artificial Intelligence — 5 papers
• Machine Learning — 5 papers
• Neural and Evolutionary Computing — 4 papers
• Image and Signal Denoising Methods — 3 papers
• Neural Networks and Applications — 3 papers
• Advanced Graph Neural Networks — 2 papers
• Sport Psychology and Performance — 2 papers
• Artificial Intelligence in Healthcare and Education — 2 papers

Highest-Cited Papers

1. FuzzPrismEdge: dynamic resource allocation in edge AI via context-aware fuzzy gating
2. ModNet-Flat: A Self-Growing Layer-Free Recurrent Network for Universal Computation An evolutionary framework that discovers structure from first principles
3. Recursive Projection Dynamics of Neural Representations: Geometry, Dimensionality, and Task Information
4. Green-ELM: Efficient Analytic Learning via High-Dimensional Random Projections
5. Building a Neural Network from Scratch: Implementation, Evaluation, and Optimization
6. Quantization robustness from dense representations of sparse functions in high-capacity kernel associative memory
7. Auditing Fairness Reliability in Tabular In-Context Learning: Composition-Matched Controls and Practical Severity
8. FCx: An algorithm for finding Feasible Counterfactual Explanations
9. FPGA-Based Fault-Tolerant Median Denoising Architecture for Impulse Noise Removal in Digital Images
10. FPGA-Based Fault-Tolerant Median Denoising Architecture for Impulse Noise Removal in Digital Images
11. Causal Inference with Video Features as Treatments
12. SAM-on-the-Curve: Sharpness-Aware Mode Connectivity for Robust Weight-Space Interpolation
13. NObSP: Functional Decomposition of Neural Networks via Oblique Subspace Projections
14. Sanity Checking Causal Representation Learning on a Simple Real-World System
15. Structured Features Overfit Where Random Features Grok
16. When Should a World Model Move? Loss-Conditioned State Execution
17. Optimal Pruning for Neural Architectures using Fisher Information Distances
18. Sharp Closure Thresholds for Two-Hidden-Layer ReLU Networks
19. Sharp Closure Thresholds for Two-Hidden-Layer ReLU Networks
20. A Question Worth Answering: What Would a Neural Network Preserve?