Neural Architecture Search On Nas Bench 201
Métriques
Accuracy (Test)
Accuracy (Val)
Search time (s)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy (Test) | Accuracy (Val) | Search time (s) |
|---|---|---|---|
| multi-conditioned-graph-diffusion-for-neural | 45.41 | 46.66 | 15.36 |
| parzc-parametric-zero-cost-proxies-for | 46.34 | 46.37 | - |
| learning-where-to-look-generative-nas-is | 46.42 | 46.73 | - |
| searching-for-a-robust-neural-architecture-in-1 | 41.71 | - | 28926 |
| a-darts-once-more-enhancing-differentiable | 46.34 | 46.17 | - |
| epe-nas-efficient-performance-estimation | 38.80 | - | 20.5 |
| neural-architecture-search-with-bayesian | 46.37 | - | 75600 |
| darts-robustly-stepping-out-of-performance | 45.12 | 44.87 | - |
| does-unsupervised-architecture-representation | 46.27 | - | - |
| shapley-nas-discovering-operation-1 | 46.85 | 46.57 | - |
| guided-evolutionary-neural-architecture | 46.04 | - | - |
| idarts-differentiable-architecture-search | 40.89 | 40.38 | - |
| progressive-neural-architecture-search | - | 44.75 | - |
| sandwich-batch-normalization-1 | 45.85 | - | - |
| darts-differentiable-architecture-search | 16.43 | - | 29902 |
| l-darts-mitigating-performance-collapse-by | 46.34 | 46.37 | - |
| local-search-is-state-of-the-art-for-nas | 46.38 | - | 151200 |
| catch-context-based-meta-reinforcement | - | 46.07 | 18000 |
| geometry-aware-gradient-algorithms-for-neural | 46.36 | - | - |
| neural-architecture-search-without-training | 38.33 | - | 1.7 |
| darts-differentiable-architecture-search | 16.43 | - | 10890 |
| efficient-neural-architecture-search-via | 16.43 | - | 13315 |
| balenas-differentiable-architecture-search | 46.54 | 46.14 | - |
| b-darts-beta-decay-regularization-for | 46.71 | - | - |
| regularized-evolution-for-image-classifier | 45.54 | - | 12000 |
| knas-green-neural-architecture-search | 45.05 | - | - |
| b-darts-beta-decay-regularization-for | 46.71 | - | - |
| neural-architecture-ranker | 46.66 | 46.16 | - |
| epe-nas-efficient-performance-estimation | 42.05 | - | 105.8 |
| drnas-dirichlet-neural-architecture-search | 46.34 | 46.37 | - |
| random-search-and-reproducibility-for-neural | 31.14 | - | 7587 |
| automatic-subspace-evoking-for-efficient | - | 46.66 | - |
| one-shot-neural-architecture-search-via-self | - | 32.52 | - |
| bananas-bayesian-optimization-with-neural | 46.3 | - | 100800 |
| when-nas-meets-trees-an-efficient-algorithm | 46.31 | - | - |
| fairnas-rethinking-evaluation-fairness-of | 42.19 | - | 9845 |
| snas-stochastic-neural-architecture-search | 43.16 | - | - |
| epe-nas-efficient-performance-estimation | 41.84 | - | 206.2 |
| du-darts-decreasing-the-uncertainty-of | 45.94 | - | - |
| neural-architecture-search-without-training | 36.37 | - | 17.4 |
| epe-nas-efficient-performance-estimation | 41.92 | - | 2.3 |
| b-darts-beta-decay-regularization-for | 46.34 | 46.37 | - |
| cr-lso-convex-neural-architecture | 46.98 | 46.51 | - |
| cyclic-differentiable-architecture-search | 45.51 | - | - |
| dsnas-direct-neural-architecture-search | - | 41.07 | - |
| differentiable-architecture-search-with-1 | 46.1 | 46.40 | - |
| is-darts-stabilizing-darts-through-precise | 46.34 | 46.37 | - |
| pre-nas-predictor-assisted-evolutionary | 45.34 | - | - |
| generic-neural-architecture-search-via | 45.59 | - | 1080 |