Research map / Label-efficient and robust learning / Domain adaptation and generalization
Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use 1 Langevin step instead of 15 (ablation) | CycleCoopNets · Apple→orange | FID: 154.58 -> 192.60 | Hurt |
| use 1 Langevin step instead of 15 (ablation) | CycleCoopNets · Apple→orange | DIPD: 1.23 -> 1.43 | Hurt |
| use 1 Langevin step instead of 15 (ablation) | CycleCoopNets · Orange→apple | FID: 118.82 -> 143.00 | Hurt |
| use 1 Langevin step instead of 15 (ablation) | CycleCoopNets · Orange→apple | DIPD: 1.25 -> 1.42 | Hurt |
| use 5 Langevin steps instead of 15 (ablation) | CycleCoopNets · Apple→orange | FID: 154.58 -> 166.41 | Hurt |
| use 5 Langevin steps instead of 15 (ablation) | CycleCoopNets · Apple→orange | DIPD: 1.23 -> 1.43 | Hurt |
| use 5 Langevin steps instead of 15 (ablation) | CycleCoopNets · Orange→apple | FID: 118.82 -> 170.38 | Hurt |
| use 5 Langevin steps instead of 15 (ablation) | CycleCoopNets · Orange→apple | DIPD: 1.25 -> 1.40 | Hurt |
| use 10 Langevin steps instead of 15 (ablation) | CycleCoopNets · Apple→orange | FID: 154.58 -> 189.60 | Hurt |
| use 10 Langevin steps instead of 15 (ablation) | CycleCoopNets · Apple→orange | DIPD: 1.23 -> 1.32 | Hurt |
| use 10 Langevin steps instead of 15 (ablation) | CycleCoopNets · Orange→apple | FID: 118.82 -> 141.60 | Hurt |
| use 10 Langevin steps instead of 15 (ablation) | CycleCoopNets · Orange→apple | DIPD: 1.25 -> 1.32 | Hurt |
Closest papers by meaning
- Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching (AAAI 2018 · similarity 0.87)
- Structure Preserving Generative Cross-Domain Learning (CVPR 2020 · similarity 0.86)
- Latent-Guided Cooperative Energy-Based Models (ICML 2026 · similarity 0.86)
- Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach (ICLR 2024 · similarity 0.84)
- End-to-End Training for Unified Tokenization and Latent Denoising (NeurIPS 2026 · similarity 0.84)
- Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency (ICLR 2024 · similarity 0.84)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.