LEARNING A SAT SOLVER FROM SINGLE-BIT SUPERVISION 2020-05-01
LEARNING A SAT SOLVER FROM SINGLE-BIT SUPERVISIONgit Abstract NeuroSAT : a classifier to predict satisfiability of a propositional formula train NN ，2* LSTM+3* MLP （每一個t ： literal & variable 相互更新） 監督學習,
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相關文章
- 1. Call Paralution Solver from Fortran
- 2. 論文筆記：Learning task-oriented grasping for tool manipulation from simulated self-supervision
- 3. SAT&SMT
- 4. Learning 3D Shape Completion from Laser Scan Data with Weak Supervision
- 5. 【原創】【論文閱讀】2020 Learning From Noisy Large-Scale Datasets With Minimal Supervision
- 6. LEARNING NOTES FROM DEEP LEARNING
- 7. Learning like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images
- 8. Learning-Pixel-level-Semantic-Affinity-with-Image-level-Supervision
- 9. Reading Note: DSOD: Learning Deeply Supervised Object Detectors from Scratch
- 10. 論文筆記：SinGAN: Learning a Generative Model from a Single Natural Image